Prognostic factors of functional outcome after hip fracture surgery: a systematic review

Prognostic factors of functional outcome after hip fracture surgery: a systematic review Abstract Objective this systematic review aimed to identify immutable and modifiable prognostic factors of functional outcomes and their proposed mechanism after hip fracture surgery. Design systematic search of MEDLINE, Embase, CINAHL, PEDRO, OpenGrey and ClinicalTrials.gov for observational studies of prognostic factors of functional outcome after hip fracture among surgically treated adults with mean age of 65 years and older. Study selection, quality assessment, and data extraction were completed independently by two reviewers. The Quality in Prognosis Studies Tool was used for quality assessment and assigning a level of evidence to factors. Proposed mechanisms for reported associations were extracted from discussion sections. Results from 33 studies of 9,552 patients, we identified 25 prognostic factors of functional outcome after hip fracture surgery. We organised factors into groups: demographics, injury and comorbidities, body composition, complications, and acute care. We assigned two factors a weak evidence level—anaemia and cognition. We assigned Parkinson’s disease an inconclusive evidence level. We could not assign an evidence level to the remaining 22 factors due to the high risk of bias across studies. Frailty was the proposed mechanism for the association between anaemia and functional outcome. Medication management, perceived potential, complications and time to mobility were proposed as mechanisms for the association between cognition and functional outcome. Conclusion we identified one modifiable and one immutable prognostic factor for functional outcomes after hip fracture surgery. Future research may target patients with anaemia or cognitive impairment by intervening on the prognostic factor or the underlying mechanisms. hip fracture, functional recovery, prognosis, systematic review, older people Introduction In the UK, 75,000 men and women over the age of 60 years are admitted to acute care with hip fracture each year [1]. The injury has been dubbed the ‘hip attack’, due to its clinical severity and adverse consequences [2]. Even with treatment, up to 10% of patients die postoperatively in hospital [3]. Among survivors, 25% never recover their prefracture function, and 22% transition from independent living to long-term care [4–6]. Clinicians take steps to improve functional outcomes changing how patients are assessed and rehabilitated after hip fracture surgery [7–9]. Yet the most effective rehabilitation remains unclear [7–9]. This uncertainty may be due to limited understanding of the extent of prognostic factors [10, 11]. For example, studies suggest sex [12], fracture type [12], surgery type [13] and time to surgery [14] are associated with functional outcomes after hip fracture. Indeed, outcomes may vary between women treated early for transcervical fracture with arthroplasty and men treated late for intertrochanteric fracture with internal fixation. Uncertainty over the most effective rehabilitation may also be due to limited understanding of the nature of prognostic factors. Prognostic factors are immutable when interventions cannot change the factor level [15]. Knowledge of immutable prognostic factors would enable clinicians to adopt a stratified care approach by prioritising those at high risk of poor functional outcomes for more intensive rehabilitation [11]. In contrast, prognostic factors are modifiable when interventions may change the factor level [15]. Indeed, in the UK, Best Practice Tariffs target modifiable prognostic factors of mortality after hip fracture surgery for health care improvement [16] No attempt has been made to synthesise the extent and nature of prognostic factors for functional outcomes after hip fracture surgery. Therefore, we conducted a systematic review of the literature to identify both modifiable and immutable prognostic factors for functional outcomes of hip fracture surgery. We further summarised these factors on the proposed underlying mechanism for the reported associations. Methods Search strategy The protocol for this systematic review was registered on the International Register of Systematic Reviews (PROSPERO) (CRD42017069148) [17]. Databases were searched for published (MEDLINE, Embase, CINAHL and PEDRO) and unpublished (OpenGrey) studies and protocols (ClinicalTrials.gov) (see Appendix 1, Supplementary data are available in Age and Ageing online). The search was developed using terms for hip fracture and functional outcome employed by previous Cochrane Systematic Reviews [18–21]. Reference lists of retrieved studies were screened to identify additional studies that may have been missed during database searches. Authors were contacted for further information, if required. Selection criteria We exported citations from databases into Covidence for de-duplication and screening [22]. Two reviewers independently screened all abstracts against inclusion and exclusion criteria (R1, R2). Conflicts were resolved by a third reviewer (R3). Full texts of potentially eligible studies were independently screened by two reviewers (R2, R3) with conflicts resolved by a third reviewer (R1). Inclusion criteria We included observational studies which reported the association between a prognostic factor and any measure of functional outcome (function, mobility or balance) on discharge from acute care. We included observational studies of adults with mean age of 65 years and older who underwent surgery after non-pathological closed hip fracture, published in English between 1 January 2007 and 30 June 2017. Exclusion criteria We excluded studies of adults with mean age <65 years, admitted with an injury other than hip fracture, treated conservatively for hip fracture, treated surgically for a pathological or open hip fracture, or which reported on non-functional outcomes or outcomes following discharge. We excluded intervention-based studies on the premise they do not reflect prognostic factors of functional outcome following usual care, as well as case studies, editorials, commentaries and conference proceedings. Quality assessment Selected studies were assessed independently for methodological quality by two reviewers (R1, R2) using the Quality in Prognosis Studies (QUIPS) tool [23]. The QUIPS tool assesses risk of bias in six domains—participation, attrition, prognostic factor measurement, outcome measurement, confounding, and statistical analysis and reporting [23]. Conflicts were resolved by consensus (R1, R2). We assigned a level of evidence for each factor according to guidelines developed by Hayden et al. ‘that studies of acceptable quality for inclusion in the synthesis would at least partly satisfy each of the six biases (that is, studies from the analysis that are at high risk for any important bias would be omitted)’ [24]. This guideline was adapted for use with the QUIPS tool by Burton et al.[25] Studies were assigned an overall high risk of bias if one or more domains were considered high risk [24]. Studies were assigned a moderate risk of bias if three or more domains were moderate risk and none were high risk [24, 25]. Studies were assigned a low risk of bias if three or more domains were low risk and none were high risk [24, 25]. Data extraction Data extraction was completed by one reviewer onto tables designed a priori (R2). All data was checked for accuracy by a second reviewer (R1). Data extracted included the author’s name, publication date, study population, age, sample size, eligibility criteria, prognostic factor measurement, outcome measurement, length of stay, analysis type and effect estimate. The proposed mechanisms for reported associations were extracted from the discussion sections by one reviewer (R1). The extraction was checked for accuracy by a second reviewer (R3). Analysis We reported study characteristics as counts and proportions. We reviewed the data extraction tables to assess for study heterogeneity. There was variation in eligibility criteria, prognostic factor measurement, and outcome measurement across studies. Therefore, we analysed the association between prognostic factors and functional outcomes using a narrative review approach [26]. We summarised the evidence on prognostic factors and their underlying mechanisms in tables. We further summarised factors and their proposed mechanisms in a dependency graph to represent relationships among assembled factors [27]. We synthesised the evidence for prognostic factors where the overall risk of bias was low [24]. Results Study selection Figure 1 presents a flow diagram of study selection. We identified 3,487 studies after de-duplication. Following title and abstract screening 155 full-text studies progressed to full-text review. We subsequently included 33 studies in this review. Figure 1. View largeDownload slide Study selection. Figure 1. View largeDownload slide Study selection. Study characteristics This systematic review included 9,552 patients (mean age 68–89 years). Sample size ranged from 55 [28] to 1114 [29] patients (Table 1). Functional outcome was measured by Functional Independence Measure in 11 studies [29–39], Barthel index in eight studies [40–47], modified Barthel index in six studies [48–53], Tinetti [44, 54] and Timed Up and Go in two studies [28, 55], and Elderly Mobility Scale [56] and Cumulated Ambulation Score [30] in one study. Four studies developed their own functional outcome measure [57–60]. Length of stay after hip fracture surgery ranged from 1 [30] to 55 [36] days across studies. Table 1. Prognostic factors assessed for association with functional outcome after hip fracture surgery Author/year Risk of bias Sample size Prognostic factor Outcome LOS (days) Effect estimates(95% CI) Adam 2013 High 90 EMS EMS, LEFS NA 1.4 (CI NA) Adunksy 2008 High NA Anaemia on discharge FIM 32 0.8 (0.3–1.8) Adunksy 2011 High 606 Change in GFR FIM 31–32 1.0 (1.0–1.0) Adunksy 2015 High 707 Post-voiding residual volume FIM 30–31 −1.8 (−3.8 to −0.2) Adunksy 2012 High 1114 Atrial fibrillation FIM 29–33 NA Arinzon 2007 High 165 VAS FIM 42–55 −6.7 (−12.2 to −1.3) Benedetti 2015 High 249 SPMSQ BI 10 0.6 Bliemel 2015 Low 402 Parkinson’s disease BI, POMA, TUG 14–17 P = 0.1 Bliemel 2015B High 402 MMSE BI 12–15 −16.1 (−21.5 to −10.5) Buecking 2015 High 392 Age, BI, CCI, anaemia on admission, MMSE, time to surgery POMA NA Age: −0.2 (−0.3 to −0.1) BI: 0.1 (0.1–0.2) CCI: −0.4 (−0.8 to −0.0) Anaemia on admission: 0.1 (0.0–0.1) MMSE: 0.2 (0.1–0.4) Time to surgery: −0.1 (−0.1 to −0.0) Doshi 2014 High 179 Age MBI 10 P > 0.05 Dubljanin-Raspopovic 2011 Low 343 Anaemia on admission FIM 31 1.3 (1.0–1.3) Dubljanin Raspopovic 2014 High 112 GDS FIM 28 GDS −0.2 (−11.5 to 0.1) Enemark 2017 High 73 Parkinson’s disease Mobility* 12 P = 0.1 Goisser 2015 High 117 Dietary intake BI 13 P = 0·003 Goisser 2015 High 117 MNA BI 5–45 P = 0.2 Gonzalez-Montalvo 2016 High 479 Sarcopenia FAC, BI 10 1.7 (0.99–2.8) Horikawa 2014 High 99 Prefracture residence ADL† 34–49 P < 0.001 Hulsbaek 2015 High 167 Age, sex, NMS, procedure type, time to mobilisation, anaemia on discharge CAS 1–18 Age: 4.3 (1.8–10.1) Sex: 0.9 (0.4–2.4) NMS: 7.0 (2.9–17.0) Procedure type: 1.6 (0.7–3.9) Time to mobilisation: 3.3(1.3–8.0) Anaemia on discharge: 5.8 (CI: NA) Kondo 2010 High 211 LOS Mobility‡ 8–44 0.2 (0.0–0.9) Kristensen 2009 High 436 Age, NMS, fracture type TUG NA Age: 0.5 (0.2–0.8) NMS: −10.8 (−16.5 to −5.0) Fracture type: 6.6 (1.9–11.1) Kristensen 2013 High 55 VAS TUG NA VAS: 8.7 (2.1–15.2)¶ Lee 2013 High 293 DVT MBI BBS NA MBI P = 0.8 BBS P = 0.2 Lieberman 2007 High 224 Diabetes FIM 29–32 P = 0.001 Liu 2015 High 261 Vitamin D BI 10–33 5.2 (3.1–8.2) Martin-Martin 2015 High 186 Age, MBI, fracture type, GHQ-28, LOS POMA NA Age: −0.1 (−0.2 to 0.1) MBI: 0.1 (0.1–0.1) Fracture type: −1.5 (−2.8 to −0.2) GHQ-28: −0.2 (−0.3 to −0.1) LOS: −0.1 (−0.1 to −0.0) Mizrahi 2007 High 449 Albumin FIM 31–32 P = 0.4 Morghen 2011 High 386 MMSE MBI 28–29 NA Morghen 2011 High 423 GDS MBI 27–29 Mild 1.6 (0.8–3.3) Moderate/Severe 1.6 (1.3–7.8) Seng 2015 High 210 Vitamin D MBI NA NA Shakouri 2009 High 117 Age, FIM, BMI, LOS FIM NA NA LOS: P > 0.05 Uriz-Otano 2015 Low 285 Prefracture function, delirium, medications, pressure ulcers, urinary retention, MMSE BI 9–10 Prefracture function: 5.6 (2.4–12.7) Delirium: 3.2 (1.1–9.5) Medications: 1.6 (1.2–2.1) ** Pressure ulcers: 11.1 (2.9–43.3) Urinary retention: 3.9 (1.0–15.0) MMSE 1.1 (1.0–1.2) Yonezawa 2009 High 203 Time to surgery Mobility§ 38–40 P = 0.04 Author/year Risk of bias Sample size Prognostic factor Outcome LOS (days) Effect estimates(95% CI) Adam 2013 High 90 EMS EMS, LEFS NA 1.4 (CI NA) Adunksy 2008 High NA Anaemia on discharge FIM 32 0.8 (0.3–1.8) Adunksy 2011 High 606 Change in GFR FIM 31–32 1.0 (1.0–1.0) Adunksy 2015 High 707 Post-voiding residual volume FIM 30–31 −1.8 (−3.8 to −0.2) Adunksy 2012 High 1114 Atrial fibrillation FIM 29–33 NA Arinzon 2007 High 165 VAS FIM 42–55 −6.7 (−12.2 to −1.3) Benedetti 2015 High 249 SPMSQ BI 10 0.6 Bliemel 2015 Low 402 Parkinson’s disease BI, POMA, TUG 14–17 P = 0.1 Bliemel 2015B High 402 MMSE BI 12–15 −16.1 (−21.5 to −10.5) Buecking 2015 High 392 Age, BI, CCI, anaemia on admission, MMSE, time to surgery POMA NA Age: −0.2 (−0.3 to −0.1) BI: 0.1 (0.1–0.2) CCI: −0.4 (−0.8 to −0.0) Anaemia on admission: 0.1 (0.0–0.1) MMSE: 0.2 (0.1–0.4) Time to surgery: −0.1 (−0.1 to −0.0) Doshi 2014 High 179 Age MBI 10 P > 0.05 Dubljanin-Raspopovic 2011 Low 343 Anaemia on admission FIM 31 1.3 (1.0–1.3) Dubljanin Raspopovic 2014 High 112 GDS FIM 28 GDS −0.2 (−11.5 to 0.1) Enemark 2017 High 73 Parkinson’s disease Mobility* 12 P = 0.1 Goisser 2015 High 117 Dietary intake BI 13 P = 0·003 Goisser 2015 High 117 MNA BI 5–45 P = 0.2 Gonzalez-Montalvo 2016 High 479 Sarcopenia FAC, BI 10 1.7 (0.99–2.8) Horikawa 2014 High 99 Prefracture residence ADL† 34–49 P < 0.001 Hulsbaek 2015 High 167 Age, sex, NMS, procedure type, time to mobilisation, anaemia on discharge CAS 1–18 Age: 4.3 (1.8–10.1) Sex: 0.9 (0.4–2.4) NMS: 7.0 (2.9–17.0) Procedure type: 1.6 (0.7–3.9) Time to mobilisation: 3.3(1.3–8.0) Anaemia on discharge: 5.8 (CI: NA) Kondo 2010 High 211 LOS Mobility‡ 8–44 0.2 (0.0–0.9) Kristensen 2009 High 436 Age, NMS, fracture type TUG NA Age: 0.5 (0.2–0.8) NMS: −10.8 (−16.5 to −5.0) Fracture type: 6.6 (1.9–11.1) Kristensen 2013 High 55 VAS TUG NA VAS: 8.7 (2.1–15.2)¶ Lee 2013 High 293 DVT MBI BBS NA MBI P = 0.8 BBS P = 0.2 Lieberman 2007 High 224 Diabetes FIM 29–32 P = 0.001 Liu 2015 High 261 Vitamin D BI 10–33 5.2 (3.1–8.2) Martin-Martin 2015 High 186 Age, MBI, fracture type, GHQ-28, LOS POMA NA Age: −0.1 (−0.2 to 0.1) MBI: 0.1 (0.1–0.1) Fracture type: −1.5 (−2.8 to −0.2) GHQ-28: −0.2 (−0.3 to −0.1) LOS: −0.1 (−0.1 to −0.0) Mizrahi 2007 High 449 Albumin FIM 31–32 P = 0.4 Morghen 2011 High 386 MMSE MBI 28–29 NA Morghen 2011 High 423 GDS MBI 27–29 Mild 1.6 (0.8–3.3) Moderate/Severe 1.6 (1.3–7.8) Seng 2015 High 210 Vitamin D MBI NA NA Shakouri 2009 High 117 Age, FIM, BMI, LOS FIM NA NA LOS: P > 0.05 Uriz-Otano 2015 Low 285 Prefracture function, delirium, medications, pressure ulcers, urinary retention, MMSE BI 9–10 Prefracture function: 5.6 (2.4–12.7) Delirium: 3.2 (1.1–9.5) Medications: 1.6 (1.2–2.1) ** Pressure ulcers: 11.1 (2.9–43.3) Urinary retention: 3.9 (1.0–15.0) MMSE 1.1 (1.0–1.2) Yonezawa 2009 High 203 Time to surgery Mobility§ 38–40 P = 0.04 Abbreviations: EMS, Elderly Mobility Score; LEFS, Lower Extremity Functional Scale; BI, Barthel Index; MBI, Modified Barthel Index; NMS, New Mobility Score; CAS, Cumulated Ambulation Score; TUG, Timed Up and Go, Tinetti Performance Orientated Mobility Assessment; MMSE, mini mental state exam; SPMSQ, short portable mental status questionnaire; MNA, mini nutritional assessment; BMI, body mass index; FAC, Functional Ambulation Category; LOS, length of stay; FIM, Functional Independence Measure; NA, not available; CI, confidence interval. *Mobility = independent—able to walk using a walker or walking stick but without the assistance from another person. Patients able to walk before hip fracture but not at discharge from the hospital were described as having ‘loss of mobility’. †ADL—1–5 1= bed rest immobilisation for 24 h, 2 = use of wheelchair with caregiver’s aid, 3 = walking possible with a walking aid at home or in a geriatric health service facility, 4 = independent gait with a T-cane aid anytime and anywhere, 5 = independent gait with no aid during daily activities. ‡Mobility 1 = walk independent without the use of equipment, 2 = walk with cane, 3 = walk with a walking frame or cart, 4 = needs assistance, 5 = use of a wheelchair and 6 = confined to bed. §Mobility 1 = independently walking without cane, 2 = single cane walker or without cane but rather unstable, 3 = with a walker, walk while holding onto something or walk with support, 4 = move by wheelchair ¶from multivariate regression which did not include fracture type as a covariate. **Walking component of BI only. Table 1. Prognostic factors assessed for association with functional outcome after hip fracture surgery Author/year Risk of bias Sample size Prognostic factor Outcome LOS (days) Effect estimates(95% CI) Adam 2013 High 90 EMS EMS, LEFS NA 1.4 (CI NA) Adunksy 2008 High NA Anaemia on discharge FIM 32 0.8 (0.3–1.8) Adunksy 2011 High 606 Change in GFR FIM 31–32 1.0 (1.0–1.0) Adunksy 2015 High 707 Post-voiding residual volume FIM 30–31 −1.8 (−3.8 to −0.2) Adunksy 2012 High 1114 Atrial fibrillation FIM 29–33 NA Arinzon 2007 High 165 VAS FIM 42–55 −6.7 (−12.2 to −1.3) Benedetti 2015 High 249 SPMSQ BI 10 0.6 Bliemel 2015 Low 402 Parkinson’s disease BI, POMA, TUG 14–17 P = 0.1 Bliemel 2015B High 402 MMSE BI 12–15 −16.1 (−21.5 to −10.5) Buecking 2015 High 392 Age, BI, CCI, anaemia on admission, MMSE, time to surgery POMA NA Age: −0.2 (−0.3 to −0.1) BI: 0.1 (0.1–0.2) CCI: −0.4 (−0.8 to −0.0) Anaemia on admission: 0.1 (0.0–0.1) MMSE: 0.2 (0.1–0.4) Time to surgery: −0.1 (−0.1 to −0.0) Doshi 2014 High 179 Age MBI 10 P > 0.05 Dubljanin-Raspopovic 2011 Low 343 Anaemia on admission FIM 31 1.3 (1.0–1.3) Dubljanin Raspopovic 2014 High 112 GDS FIM 28 GDS −0.2 (−11.5 to 0.1) Enemark 2017 High 73 Parkinson’s disease Mobility* 12 P = 0.1 Goisser 2015 High 117 Dietary intake BI 13 P = 0·003 Goisser 2015 High 117 MNA BI 5–45 P = 0.2 Gonzalez-Montalvo 2016 High 479 Sarcopenia FAC, BI 10 1.7 (0.99–2.8) Horikawa 2014 High 99 Prefracture residence ADL† 34–49 P < 0.001 Hulsbaek 2015 High 167 Age, sex, NMS, procedure type, time to mobilisation, anaemia on discharge CAS 1–18 Age: 4.3 (1.8–10.1) Sex: 0.9 (0.4–2.4) NMS: 7.0 (2.9–17.0) Procedure type: 1.6 (0.7–3.9) Time to mobilisation: 3.3(1.3–8.0) Anaemia on discharge: 5.8 (CI: NA) Kondo 2010 High 211 LOS Mobility‡ 8–44 0.2 (0.0–0.9) Kristensen 2009 High 436 Age, NMS, fracture type TUG NA Age: 0.5 (0.2–0.8) NMS: −10.8 (−16.5 to −5.0) Fracture type: 6.6 (1.9–11.1) Kristensen 2013 High 55 VAS TUG NA VAS: 8.7 (2.1–15.2)¶ Lee 2013 High 293 DVT MBI BBS NA MBI P = 0.8 BBS P = 0.2 Lieberman 2007 High 224 Diabetes FIM 29–32 P = 0.001 Liu 2015 High 261 Vitamin D BI 10–33 5.2 (3.1–8.2) Martin-Martin 2015 High 186 Age, MBI, fracture type, GHQ-28, LOS POMA NA Age: −0.1 (−0.2 to 0.1) MBI: 0.1 (0.1–0.1) Fracture type: −1.5 (−2.8 to −0.2) GHQ-28: −0.2 (−0.3 to −0.1) LOS: −0.1 (−0.1 to −0.0) Mizrahi 2007 High 449 Albumin FIM 31–32 P = 0.4 Morghen 2011 High 386 MMSE MBI 28–29 NA Morghen 2011 High 423 GDS MBI 27–29 Mild 1.6 (0.8–3.3) Moderate/Severe 1.6 (1.3–7.8) Seng 2015 High 210 Vitamin D MBI NA NA Shakouri 2009 High 117 Age, FIM, BMI, LOS FIM NA NA LOS: P > 0.05 Uriz-Otano 2015 Low 285 Prefracture function, delirium, medications, pressure ulcers, urinary retention, MMSE BI 9–10 Prefracture function: 5.6 (2.4–12.7) Delirium: 3.2 (1.1–9.5) Medications: 1.6 (1.2–2.1) ** Pressure ulcers: 11.1 (2.9–43.3) Urinary retention: 3.9 (1.0–15.0) MMSE 1.1 (1.0–1.2) Yonezawa 2009 High 203 Time to surgery Mobility§ 38–40 P = 0.04 Author/year Risk of bias Sample size Prognostic factor Outcome LOS (days) Effect estimates(95% CI) Adam 2013 High 90 EMS EMS, LEFS NA 1.4 (CI NA) Adunksy 2008 High NA Anaemia on discharge FIM 32 0.8 (0.3–1.8) Adunksy 2011 High 606 Change in GFR FIM 31–32 1.0 (1.0–1.0) Adunksy 2015 High 707 Post-voiding residual volume FIM 30–31 −1.8 (−3.8 to −0.2) Adunksy 2012 High 1114 Atrial fibrillation FIM 29–33 NA Arinzon 2007 High 165 VAS FIM 42–55 −6.7 (−12.2 to −1.3) Benedetti 2015 High 249 SPMSQ BI 10 0.6 Bliemel 2015 Low 402 Parkinson’s disease BI, POMA, TUG 14–17 P = 0.1 Bliemel 2015B High 402 MMSE BI 12–15 −16.1 (−21.5 to −10.5) Buecking 2015 High 392 Age, BI, CCI, anaemia on admission, MMSE, time to surgery POMA NA Age: −0.2 (−0.3 to −0.1) BI: 0.1 (0.1–0.2) CCI: −0.4 (−0.8 to −0.0) Anaemia on admission: 0.1 (0.0–0.1) MMSE: 0.2 (0.1–0.4) Time to surgery: −0.1 (−0.1 to −0.0) Doshi 2014 High 179 Age MBI 10 P > 0.05 Dubljanin-Raspopovic 2011 Low 343 Anaemia on admission FIM 31 1.3 (1.0–1.3) Dubljanin Raspopovic 2014 High 112 GDS FIM 28 GDS −0.2 (−11.5 to 0.1) Enemark 2017 High 73 Parkinson’s disease Mobility* 12 P = 0.1 Goisser 2015 High 117 Dietary intake BI 13 P = 0·003 Goisser 2015 High 117 MNA BI 5–45 P = 0.2 Gonzalez-Montalvo 2016 High 479 Sarcopenia FAC, BI 10 1.7 (0.99–2.8) Horikawa 2014 High 99 Prefracture residence ADL† 34–49 P < 0.001 Hulsbaek 2015 High 167 Age, sex, NMS, procedure type, time to mobilisation, anaemia on discharge CAS 1–18 Age: 4.3 (1.8–10.1) Sex: 0.9 (0.4–2.4) NMS: 7.0 (2.9–17.0) Procedure type: 1.6 (0.7–3.9) Time to mobilisation: 3.3(1.3–8.0) Anaemia on discharge: 5.8 (CI: NA) Kondo 2010 High 211 LOS Mobility‡ 8–44 0.2 (0.0–0.9) Kristensen 2009 High 436 Age, NMS, fracture type TUG NA Age: 0.5 (0.2–0.8) NMS: −10.8 (−16.5 to −5.0) Fracture type: 6.6 (1.9–11.1) Kristensen 2013 High 55 VAS TUG NA VAS: 8.7 (2.1–15.2)¶ Lee 2013 High 293 DVT MBI BBS NA MBI P = 0.8 BBS P = 0.2 Lieberman 2007 High 224 Diabetes FIM 29–32 P = 0.001 Liu 2015 High 261 Vitamin D BI 10–33 5.2 (3.1–8.2) Martin-Martin 2015 High 186 Age, MBI, fracture type, GHQ-28, LOS POMA NA Age: −0.1 (−0.2 to 0.1) MBI: 0.1 (0.1–0.1) Fracture type: −1.5 (−2.8 to −0.2) GHQ-28: −0.2 (−0.3 to −0.1) LOS: −0.1 (−0.1 to −0.0) Mizrahi 2007 High 449 Albumin FIM 31–32 P = 0.4 Morghen 2011 High 386 MMSE MBI 28–29 NA Morghen 2011 High 423 GDS MBI 27–29 Mild 1.6 (0.8–3.3) Moderate/Severe 1.6 (1.3–7.8) Seng 2015 High 210 Vitamin D MBI NA NA Shakouri 2009 High 117 Age, FIM, BMI, LOS FIM NA NA LOS: P > 0.05 Uriz-Otano 2015 Low 285 Prefracture function, delirium, medications, pressure ulcers, urinary retention, MMSE BI 9–10 Prefracture function: 5.6 (2.4–12.7) Delirium: 3.2 (1.1–9.5) Medications: 1.6 (1.2–2.1) ** Pressure ulcers: 11.1 (2.9–43.3) Urinary retention: 3.9 (1.0–15.0) MMSE 1.1 (1.0–1.2) Yonezawa 2009 High 203 Time to surgery Mobility§ 38–40 P = 0.04 Abbreviations: EMS, Elderly Mobility Score; LEFS, Lower Extremity Functional Scale; BI, Barthel Index; MBI, Modified Barthel Index; NMS, New Mobility Score; CAS, Cumulated Ambulation Score; TUG, Timed Up and Go, Tinetti Performance Orientated Mobility Assessment; MMSE, mini mental state exam; SPMSQ, short portable mental status questionnaire; MNA, mini nutritional assessment; BMI, body mass index; FAC, Functional Ambulation Category; LOS, length of stay; FIM, Functional Independence Measure; NA, not available; CI, confidence interval. *Mobility = independent—able to walk using a walker or walking stick but without the assistance from another person. Patients able to walk before hip fracture but not at discharge from the hospital were described as having ‘loss of mobility’. †ADL—1–5 1= bed rest immobilisation for 24 h, 2 = use of wheelchair with caregiver’s aid, 3 = walking possible with a walking aid at home or in a geriatric health service facility, 4 = independent gait with a T-cane aid anytime and anywhere, 5 = independent gait with no aid during daily activities. ‡Mobility 1 = walk independent without the use of equipment, 2 = walk with cane, 3 = walk with a walking frame or cart, 4 = needs assistance, 5 = use of a wheelchair and 6 = confined to bed. §Mobility 1 = independently walking without cane, 2 = single cane walker or without cane but rather unstable, 3 = with a walker, walk while holding onto something or walk with support, 4 = move by wheelchair ¶from multivariate regression which did not include fracture type as a covariate. **Walking component of BI only. Quality assessment The results of the quality assessment are presented in Appendix 2, Supplementary data are available in Age and Ageing online. The agreement between two independent reviewers regarding the risk of bias domains was 90%. Following discussion 100% consensus was reached. In total, three studies (9%) had low overall risk of bias [33, 42, 44] and 30 studies (91%) had high overall risk of bias [28–32, 34–41, 43, 45–60]. The main reasons for high bias assignment were study confounding, participation, and attrition. Failure to control for important potential confounders (e.g. prefracture function, comorbidity) was a high risk of bias in 13 studies (39%) [30, 31, 35, 40, 43, 48, 50–54, 57, 59]. Overall, nine studies (27%) did not adjust for any potential confounders [30, 31, 40, 43, 51, 52, 57–59]. For 21 studies (64%) participant eligibility criteria were narrow [28, 30–32, 34–39, 45–50, 52, 53, 55, 59, 60]. In particular, eight studies (24%) excluded patients with cognitive impairment [31, 36–38, 48, 49, 51, 53]. Additional detail on participant exclusions may be found in Appendices 3–8, Supplementary data are available in Age and Ageing online. A total of six studies (18%) failed to provide reasons for loss to follow-up, or a comparison between those lost to follow-up and those observed for the study duration [41, 48, 50, 51, 55, 60]. Prognostic factors Overall, 25 prognostic factors of functional outcome after hip fracture surgery were identified by 33 studies (Table 1). Three factors were reported by studies with low overall risk of bias. We assigned a weak level of evidence for an association between functional outcome and cognitive impairment [42], and between functional outcome and anaemia on admission [33]. We assigned an inconclusive level of evidence for an association between functional outcome and Parkinson’s disease [44]. Prefracture function [42, 49], perceived potential [49], medication management [42], complications [42] and time to mobilisation [30] were proposed as underlying mechanisms for the association between cognitive impairment and functional outcome. Frailty and weakness were proposed as underlying mechanisms for the association between anaemia on admission and functional outcome [33]. Medication management and complications were proposed as underlying mechanisms for the association between Parkinson’s disease and functional outcome (Table 2 and Figure 2) [58]. Table 2. Proposed mechanisms and mediators for the functional outcome effect of prognostic factors Factor Mechanism Mediator Age Functional impairment increases with age [52]. Prefracture function Cognitive impairment increases with age [42]. Cognitive impairment Pain scores decrease with age. Older patients may be more likely to accept the pain medication provided by their health professionals is appropriate than younger patients [28]. Pain Sex Women more often present with depression than men [37]. Depression For women, urinary retention is associated with functional outcome [35]. Urinary retention Women with hip fracture are older than men [37]. Age Women present with more comorbidities than men [37]. Comorbidity count Women present with more cognitive impairment than men [37]. Cognitive impairment Prefracture residence Patients admitted from long-term care present with more cognitive impairment than those admitted from home [59]. Cognitive impairment Patients admitted from long-term care present with more comorbidities than those from home [53]. Comorbidity count Patients admitted from long-term care develop more complications than those from home [53]. Complications Patients admitted from long-term care are less likely to undergo early mobilisation than those from home [53, 59]. Time to mobilisation Comorbidity count Cognitive impairment increases with comorbidity count [42]. Cognitive impairment Length of stay increases with comorbidity count [53]. Length of stay Patients with more comorbidities are less likely to undergo early mobilisation than those with less comorbidities [30]. Time to mobilisation Diabetes Patients with diabetes are more likely to develop postoperative urinary retention than those without diabetes [35]. Complications Patients with diabetes are more likely to present with history of stroke than those without diabetes [38]. Stroke history Patients with diabetes present with less prefracture function than those without diabetes [38]. Prefracture function Cognitive impairment For patients with cognitive impairment, prefracture function is associated with functional outcome [42, 49]. Prefracture function Patients with cognitive impairment may be seen to have less potential and therapists may reduce the intensity of rehabilitation compared to patients without cognitive impairment [49]. Perceived potential Patients with cognitive impairment present on more medications than those without cognitive impairment [42]. Medication management Patients with cognitive impairment develop more complications than those without cognitive impairment [42]. Complications Patients with cognitive impairment are less likely to mobilise early than those without cognitive impairment [30]. Time to mobilisation Vitamin D Skeletal muscles require vitamin D for structural maintenance and optimal function, with deficiency causing loss of muscle mass, atrophy of type II muscle fibres and weakness [47]. Weakness Parkinson’s Disease Patients with Parkinson’s disease may not receive medication on time with some omitted completely [58]. Medication management Patients with Parkinson’s disease develop more complications than those without Parkinson’s disease [58]. Complications Dehydration Increased urea production may reflect dehydration due to bleeding around the fracture site [34]. Blood urea Malnutrition Increased urea production is associated with malnutrition [34]. Blood urea Patients with malnourishment have more comorbidities than well-nourished patients [45]. Comorbidities Patients with malnourishment are more likely to have cognitive impairment than well-nourished patients [45]. Cognitive impairment Patients with malnourishment develop more complications than well-nourished patients [46]. Complications Patients with malnourishment are more likely to be frail than well-nourished patients[46]. Frailty Depression Patients with depression may be less likely to comply with rehabilitation than those without depression [36, 48, 54]. Adherence For patients with depression, pain is associated with functional outcome [36]. Pain Patients with depression are more likely to be frail than patients without depression [37]. Frailty Therapists reduce rehabilitation intensity more for patients with depression than those without depression [37, 48]. Perceived potential Fracture type Patients with a trochanteric hip fracture require more pain medication than those with femoral neck fractures [28]. Pain Patients with more severe fractures are less likely to mobilise early than those with less severe fractures [30]. Time to mobilisation Anaemia on admission Patients with low haemoglobin on admission are more likely to be frail than those with higher haemoglobin [33]. Frailty Patients with low haemoglobin on admission may have less strength than those with higher haemoglobin [33]. Weakness Time to surgery Patients with longer time to surgery have a longer time to mobilisation than those with shorter time to surgery [54]. Time to mobilisation Complications Patients with complications have a longer acute hospital stay than those without complications [53]. Length of stay Patients with complications wait longer before mobilising than those without complications [53]. Time to mobilisation Pain Patients with pain are less likely to adhere to rehabilitation than those without pain [36]. Adherence Patients with pain are less likely to undergo early mobilisation than those without pain [30]. Time to mobilisation Patients with pain are more likely to have disturbed sleep, appetite loss, and fatigue than those without pain [36]. Fatigue Patients who report pain are less likely to be cognitively impaired than those who do not report pain [36]. Cognitive impairment Factor Mechanism Mediator Age Functional impairment increases with age [52]. Prefracture function Cognitive impairment increases with age [42]. Cognitive impairment Pain scores decrease with age. Older patients may be more likely to accept the pain medication provided by their health professionals is appropriate than younger patients [28]. Pain Sex Women more often present with depression than men [37]. Depression For women, urinary retention is associated with functional outcome [35]. Urinary retention Women with hip fracture are older than men [37]. Age Women present with more comorbidities than men [37]. Comorbidity count Women present with more cognitive impairment than men [37]. Cognitive impairment Prefracture residence Patients admitted from long-term care present with more cognitive impairment than those admitted from home [59]. Cognitive impairment Patients admitted from long-term care present with more comorbidities than those from home [53]. Comorbidity count Patients admitted from long-term care develop more complications than those from home [53]. Complications Patients admitted from long-term care are less likely to undergo early mobilisation than those from home [53, 59]. Time to mobilisation Comorbidity count Cognitive impairment increases with comorbidity count [42]. Cognitive impairment Length of stay increases with comorbidity count [53]. Length of stay Patients with more comorbidities are less likely to undergo early mobilisation than those with less comorbidities [30]. Time to mobilisation Diabetes Patients with diabetes are more likely to develop postoperative urinary retention than those without diabetes [35]. Complications Patients with diabetes are more likely to present with history of stroke than those without diabetes [38]. Stroke history Patients with diabetes present with less prefracture function than those without diabetes [38]. Prefracture function Cognitive impairment For patients with cognitive impairment, prefracture function is associated with functional outcome [42, 49]. Prefracture function Patients with cognitive impairment may be seen to have less potential and therapists may reduce the intensity of rehabilitation compared to patients without cognitive impairment [49]. Perceived potential Patients with cognitive impairment present on more medications than those without cognitive impairment [42]. Medication management Patients with cognitive impairment develop more complications than those without cognitive impairment [42]. Complications Patients with cognitive impairment are less likely to mobilise early than those without cognitive impairment [30]. Time to mobilisation Vitamin D Skeletal muscles require vitamin D for structural maintenance and optimal function, with deficiency causing loss of muscle mass, atrophy of type II muscle fibres and weakness [47]. Weakness Parkinson’s Disease Patients with Parkinson’s disease may not receive medication on time with some omitted completely [58]. Medication management Patients with Parkinson’s disease develop more complications than those without Parkinson’s disease [58]. Complications Dehydration Increased urea production may reflect dehydration due to bleeding around the fracture site [34]. Blood urea Malnutrition Increased urea production is associated with malnutrition [34]. Blood urea Patients with malnourishment have more comorbidities than well-nourished patients [45]. Comorbidities Patients with malnourishment are more likely to have cognitive impairment than well-nourished patients [45]. Cognitive impairment Patients with malnourishment develop more complications than well-nourished patients [46]. Complications Patients with malnourishment are more likely to be frail than well-nourished patients[46]. Frailty Depression Patients with depression may be less likely to comply with rehabilitation than those without depression [36, 48, 54]. Adherence For patients with depression, pain is associated with functional outcome [36]. Pain Patients with depression are more likely to be frail than patients without depression [37]. Frailty Therapists reduce rehabilitation intensity more for patients with depression than those without depression [37, 48]. Perceived potential Fracture type Patients with a trochanteric hip fracture require more pain medication than those with femoral neck fractures [28]. Pain Patients with more severe fractures are less likely to mobilise early than those with less severe fractures [30]. Time to mobilisation Anaemia on admission Patients with low haemoglobin on admission are more likely to be frail than those with higher haemoglobin [33]. Frailty Patients with low haemoglobin on admission may have less strength than those with higher haemoglobin [33]. Weakness Time to surgery Patients with longer time to surgery have a longer time to mobilisation than those with shorter time to surgery [54]. Time to mobilisation Complications Patients with complications have a longer acute hospital stay than those without complications [53]. Length of stay Patients with complications wait longer before mobilising than those without complications [53]. Time to mobilisation Pain Patients with pain are less likely to adhere to rehabilitation than those without pain [36]. Adherence Patients with pain are less likely to undergo early mobilisation than those without pain [30]. Time to mobilisation Patients with pain are more likely to have disturbed sleep, appetite loss, and fatigue than those without pain [36]. Fatigue Patients who report pain are less likely to be cognitively impaired than those who do not report pain [36]. Cognitive impairment Table 2. Proposed mechanisms and mediators for the functional outcome effect of prognostic factors Factor Mechanism Mediator Age Functional impairment increases with age [52]. Prefracture function Cognitive impairment increases with age [42]. Cognitive impairment Pain scores decrease with age. Older patients may be more likely to accept the pain medication provided by their health professionals is appropriate than younger patients [28]. Pain Sex Women more often present with depression than men [37]. Depression For women, urinary retention is associated with functional outcome [35]. Urinary retention Women with hip fracture are older than men [37]. Age Women present with more comorbidities than men [37]. Comorbidity count Women present with more cognitive impairment than men [37]. Cognitive impairment Prefracture residence Patients admitted from long-term care present with more cognitive impairment than those admitted from home [59]. Cognitive impairment Patients admitted from long-term care present with more comorbidities than those from home [53]. Comorbidity count Patients admitted from long-term care develop more complications than those from home [53]. Complications Patients admitted from long-term care are less likely to undergo early mobilisation than those from home [53, 59]. Time to mobilisation Comorbidity count Cognitive impairment increases with comorbidity count [42]. Cognitive impairment Length of stay increases with comorbidity count [53]. Length of stay Patients with more comorbidities are less likely to undergo early mobilisation than those with less comorbidities [30]. Time to mobilisation Diabetes Patients with diabetes are more likely to develop postoperative urinary retention than those without diabetes [35]. Complications Patients with diabetes are more likely to present with history of stroke than those without diabetes [38]. Stroke history Patients with diabetes present with less prefracture function than those without diabetes [38]. Prefracture function Cognitive impairment For patients with cognitive impairment, prefracture function is associated with functional outcome [42, 49]. Prefracture function Patients with cognitive impairment may be seen to have less potential and therapists may reduce the intensity of rehabilitation compared to patients without cognitive impairment [49]. Perceived potential Patients with cognitive impairment present on more medications than those without cognitive impairment [42]. Medication management Patients with cognitive impairment develop more complications than those without cognitive impairment [42]. Complications Patients with cognitive impairment are less likely to mobilise early than those without cognitive impairment [30]. Time to mobilisation Vitamin D Skeletal muscles require vitamin D for structural maintenance and optimal function, with deficiency causing loss of muscle mass, atrophy of type II muscle fibres and weakness [47]. Weakness Parkinson’s Disease Patients with Parkinson’s disease may not receive medication on time with some omitted completely [58]. Medication management Patients with Parkinson’s disease develop more complications than those without Parkinson’s disease [58]. Complications Dehydration Increased urea production may reflect dehydration due to bleeding around the fracture site [34]. Blood urea Malnutrition Increased urea production is associated with malnutrition [34]. Blood urea Patients with malnourishment have more comorbidities than well-nourished patients [45]. Comorbidities Patients with malnourishment are more likely to have cognitive impairment than well-nourished patients [45]. Cognitive impairment Patients with malnourishment develop more complications than well-nourished patients [46]. Complications Patients with malnourishment are more likely to be frail than well-nourished patients[46]. Frailty Depression Patients with depression may be less likely to comply with rehabilitation than those without depression [36, 48, 54]. Adherence For patients with depression, pain is associated with functional outcome [36]. Pain Patients with depression are more likely to be frail than patients without depression [37]. Frailty Therapists reduce rehabilitation intensity more for patients with depression than those without depression [37, 48]. Perceived potential Fracture type Patients with a trochanteric hip fracture require more pain medication than those with femoral neck fractures [28]. Pain Patients with more severe fractures are less likely to mobilise early than those with less severe fractures [30]. Time to mobilisation Anaemia on admission Patients with low haemoglobin on admission are more likely to be frail than those with higher haemoglobin [33]. Frailty Patients with low haemoglobin on admission may have less strength than those with higher haemoglobin [33]. Weakness Time to surgery Patients with longer time to surgery have a longer time to mobilisation than those with shorter time to surgery [54]. Time to mobilisation Complications Patients with complications have a longer acute hospital stay than those without complications [53]. Length of stay Patients with complications wait longer before mobilising than those without complications [53]. Time to mobilisation Pain Patients with pain are less likely to adhere to rehabilitation than those without pain [36]. Adherence Patients with pain are less likely to undergo early mobilisation than those without pain [30]. Time to mobilisation Patients with pain are more likely to have disturbed sleep, appetite loss, and fatigue than those without pain [36]. Fatigue Patients who report pain are less likely to be cognitively impaired than those who do not report pain [36]. Cognitive impairment Factor Mechanism Mediator Age Functional impairment increases with age [52]. Prefracture function Cognitive impairment increases with age [42]. Cognitive impairment Pain scores decrease with age. Older patients may be more likely to accept the pain medication provided by their health professionals is appropriate than younger patients [28]. Pain Sex Women more often present with depression than men [37]. Depression For women, urinary retention is associated with functional outcome [35]. Urinary retention Women with hip fracture are older than men [37]. Age Women present with more comorbidities than men [37]. Comorbidity count Women present with more cognitive impairment than men [37]. Cognitive impairment Prefracture residence Patients admitted from long-term care present with more cognitive impairment than those admitted from home [59]. Cognitive impairment Patients admitted from long-term care present with more comorbidities than those from home [53]. Comorbidity count Patients admitted from long-term care develop more complications than those from home [53]. Complications Patients admitted from long-term care are less likely to undergo early mobilisation than those from home [53, 59]. Time to mobilisation Comorbidity count Cognitive impairment increases with comorbidity count [42]. Cognitive impairment Length of stay increases with comorbidity count [53]. Length of stay Patients with more comorbidities are less likely to undergo early mobilisation than those with less comorbidities [30]. Time to mobilisation Diabetes Patients with diabetes are more likely to develop postoperative urinary retention than those without diabetes [35]. Complications Patients with diabetes are more likely to present with history of stroke than those without diabetes [38]. Stroke history Patients with diabetes present with less prefracture function than those without diabetes [38]. Prefracture function Cognitive impairment For patients with cognitive impairment, prefracture function is associated with functional outcome [42, 49]. Prefracture function Patients with cognitive impairment may be seen to have less potential and therapists may reduce the intensity of rehabilitation compared to patients without cognitive impairment [49]. Perceived potential Patients with cognitive impairment present on more medications than those without cognitive impairment [42]. Medication management Patients with cognitive impairment develop more complications than those without cognitive impairment [42]. Complications Patients with cognitive impairment are less likely to mobilise early than those without cognitive impairment [30]. Time to mobilisation Vitamin D Skeletal muscles require vitamin D for structural maintenance and optimal function, with deficiency causing loss of muscle mass, atrophy of type II muscle fibres and weakness [47]. Weakness Parkinson’s Disease Patients with Parkinson’s disease may not receive medication on time with some omitted completely [58]. Medication management Patients with Parkinson’s disease develop more complications than those without Parkinson’s disease [58]. Complications Dehydration Increased urea production may reflect dehydration due to bleeding around the fracture site [34]. Blood urea Malnutrition Increased urea production is associated with malnutrition [34]. Blood urea Patients with malnourishment have more comorbidities than well-nourished patients [45]. Comorbidities Patients with malnourishment are more likely to have cognitive impairment than well-nourished patients [45]. Cognitive impairment Patients with malnourishment develop more complications than well-nourished patients [46]. Complications Patients with malnourishment are more likely to be frail than well-nourished patients[46]. Frailty Depression Patients with depression may be less likely to comply with rehabilitation than those without depression [36, 48, 54]. Adherence For patients with depression, pain is associated with functional outcome [36]. Pain Patients with depression are more likely to be frail than patients without depression [37]. Frailty Therapists reduce rehabilitation intensity more for patients with depression than those without depression [37, 48]. Perceived potential Fracture type Patients with a trochanteric hip fracture require more pain medication than those with femoral neck fractures [28]. Pain Patients with more severe fractures are less likely to mobilise early than those with less severe fractures [30]. Time to mobilisation Anaemia on admission Patients with low haemoglobin on admission are more likely to be frail than those with higher haemoglobin [33]. Frailty Patients with low haemoglobin on admission may have less strength than those with higher haemoglobin [33]. Weakness Time to surgery Patients with longer time to surgery have a longer time to mobilisation than those with shorter time to surgery [54]. Time to mobilisation Complications Patients with complications have a longer acute hospital stay than those without complications [53]. Length of stay Patients with complications wait longer before mobilising than those without complications [53]. Time to mobilisation Pain Patients with pain are less likely to adhere to rehabilitation than those without pain [36]. Adherence Patients with pain are less likely to undergo early mobilisation than those without pain [30]. Time to mobilisation Patients with pain are more likely to have disturbed sleep, appetite loss, and fatigue than those without pain [36]. Fatigue Patients who report pain are less likely to be cognitively impaired than those who do not report pain [36]. Cognitive impairment Figure 2. View largeDownload slide Prognostic factors and their proposed underling mechanisms for their association with functional outcome after hip fracture surgery. Nodes represent factors and their underlying mechanisms while arrows represent dependencies between nodes. Figure 2. View largeDownload slide Prognostic factors and their proposed underling mechanisms for their association with functional outcome after hip fracture surgery. Nodes represent factors and their underlying mechanisms while arrows represent dependencies between nodes. We organised the remaining 22 factors reported by studies of high risk of bias into five groups: demographics, injury and comorbidities, body composition, complications and acute care factors. A total of 38 potential underlying mechanisms were proposed for 14 factors (Table 2 and Figure 2). Demographics: Age [30, 31, 53–55], sex [30] and prefracture residence [59] were associated with functional outcome. Age [52] and sex [55] were also reported as not associated with functional outcome. Prefracture function [52], cognitive impairment [42], and pain [28] were proposed as underlying mechanism for the association between age and functional outcome. Depression [37], urinary retention [35], age [37], comorbidity [37] and cognitive impairment [37] were proposed as underlying mechanisms for the association between sex and functional outcome. Cognitive impairment [59], comorbidity [53], complications [53] and time to mobilisation [53, 59] were proposed as underlying mechanisms for the association between prefracture residence and functional outcome (Table 2 and Figure 2). Injury and comorbidities: Fracture type was associated with functional outcome after hip fracture surgery [53, 55]. Comorbidity as measured by Charlson Comorbidity Index was associated with functional outcome after hip fracture surgery [54]. Prefracture function [30, 31, 42, 53–56], diabetes [38], atrial fibrillation [29] and vitamin D level [47] were associated with poor functional outcome after hip fracture surgery. Polypharmacy was also associated with functional outcome [42]. Vitamin D level [50] was also reported as not associated with functional outcome. Pain [28] and time to mobilisation [30] were proposed as underlying mechanisms for the association between fracture type and functional outcome. Prefracture function [38], history of stroke [38] and complications [35] were proposed as underlying mechanisms for the association between diabetes and functional outcome. Weakness was the proposed underlying mechanism for the association between vitamin D and functional outcome (Table 2 and Figure 2) [47]. Body composition body mass index [31] and malnutrition [45, 46], were associated with functional outcome after hip fracture surgery. Sarcopenia was not associated with postoperative functional outcome [43]. Comorbidity [45], cognitive impairment [45], complications [46] and frailty [46] were proposed as underlying mechanisms for the association between malnutrition and functional outcome (Table 2 and Figure 2). Complications pain [36, 55], elevated blood urea [34, 35], perioperative urinary retention [34, 35, 42], pressure ulcers [42] and delirium [42] were associated with functional outcome. Emotional distress [53] and new onset depression [37, 49] were associated with functional outcome after hip fracture surgery. Deep vein thrombosis and anaemia on discharge [30, 32] were not associated with functional outcome [51]. Admission albumin level was not associated with functional outcome [39]. Pain [36], frailty [37], perceived rehabilitation potential [37, 48] and rehabilitation adherence [36, 48, 54] were proposed as underlying mechanisms for the association between new onset depression and functional outcome. Fatigue [36], cognitive impairment [36], time to mobilisation [30] and rehabilitation adherence [36] were proposed as underlying mechanisms for the association between pain and functional outcome. Malnutrition and dehydration were proposed as underlying mechanisms for the association between blood urea and functional outcome (Table 2 and Figure 2) [34]. Acute care factors Time to surgery [54, 57], time to mobilisation [30] and overall length of stay [53, 60] were associated with functional outcome. Length of stay [31] and procedure type [30] were also reported as not associated with functional outcome. Time to mobilisation was the proposed underlying mechanism for the association between time to surgery and functional outcome (Table 2 and Figure 2) [54]. Discussion We identified 25 prognostic factors of functional outcome after hip fracture surgery from 33 studies. We organised these factors into five groups; demographics, injury and comorbidities, body composition, complications and acute care factors. Overall, the risk of bias across studies was high. There was sufficient quality evidence to assign a weak level of evidence for anaemia on admission and cognitive impairment, and an inconclusive level of evidence for Parkinson’s disease. There was insufficient quality evidence to assign a level of evidence for the remaining 22 prognostic factors. Most studies included in this review focused on immutable factors of functional outcome after hip fracture surgery. Knowledge of these factors enables clinicians to adopt a stratified care approach by prioritising those at high risk of poor outcome [11]. We assigned a weak level of evidence for an association between cognitive impairment and functional outcome. A recent systematic review reported a positive association between rehabilitation and functional outcome after hip fracture surgery among patients with cognitive impairment [61]. Despite this cognitively impaired patients are often excluded from trials of new interventions [62]. While the presence of cognitive impairment may be considered an immutable factor [63], all four proposed underlying mechanisms are modifiable—medication management, perceived potential, occurrence of complications and time to mobilisation. Future high-quality prognostic studies are required to confirm or refute the proposed underlying mechanism for the reported association. Less studies focused on modifiable factors of functional outcomes after hip fracture surgery. To inform future Best Practice Tariffs there is a need for greater understanding of modifiable prognostic factors of functional outcomes such as rehabilitation access or staffing levels. We assigned a weak level of evidence for an association between anaemia on admission and functional outcome. However, a recent randomised controlled trial indicated that a more liberal blood transfusion policy did not lead to better recovery of activities of daily living than a more restrictive blood transfusion policy [64]. In the current review frailty and weakness (a feature of frailty) were proposed as underlying mechanisms for the reported association. Alone, a more liberal transfusion policy may be an insufficient intervention to target both anaemia and frailty. A complex intervention combining transfusion with more intensive rehabilitation may warrant further study. The dependency graph presented here provides a framework for further discussion of prognostic factors and proposed mechanisms underlying their reported association with functional outcome after hip fracture surgery. In this review, the graph was constructed explicitly on existing literature. Therefore, the absence of nodes, or arrows between nodes, could reflect the absence of knowledge rather than the absence of dependency [65, 66]. For example, some may argue frailty is an underrepresented mechanism for the association between several factors and functional outcome. Indeed, frail adults are more likely to present as older, with cognitive impairment, incontinence, comorbidities and poor prefracture function compared to their nonfrail counterparts [67]. Further, there was no reference to access and delivery of rehabilitation, or participation in rehabilitation, as potential mediators for the association between factors and functional outcome. This is despite evidence for an association between depression and cognitive impairment with rehabilitation participation [68]. In fact, only 16 of the 25 factors identified included any proposed mechanism underlying the studied association. We suggest this synthesis of factors on their underlying mechanisms is an important step towards transparency about underlying assumptions in prognostic analyses. Limitations The studies included in this review focused on prognostic factors of functional outcome on discharge after hip fracture surgery. Yet, focusing solely on functional outcome overlooks other forces influencing when and if a positive functional outcome occurs. Indeed, a positive functional outcome by discharge also depends on the death rate as patients may only recover if they remain alive [69]. Further, functional outcome on discharge also depends on the length of hospital stay, which varied across studies (range 1–55 days). Poor functional outcomes could reflect a higher discharge rate rather than a true difference in functional outcomes after hip fracture surgery [69]. We assigned a level of evidence to only three prognostic factors due to the high risk of bias seen across studies. It was not possible to complete a meta-analysis due to variation in eligibility criteria, prognostic factor measurement and outcome measurement. Several studies from the same patient cohort reported a positive association between prognostic factors and functional outcomes. This may suggest publication bias [25]. To reduce this potential bias we sought to include unpublished and incomplete studies. However, we identified no grey literature or incomplete studies. Additional studies may be indexed in databases not included in our search strategy. We included search terms for function, mobility and balance. We did not include search terms for surrogate measures of functional recovery, e.g., discharge destination. Additional prognostic factors may be identified by inclusion of these surrogate measures. Finally, we limited length of follow up to discharge from hospital to reduce the likelihood of unobserved factors confounding or interacting with functional outcomes after discharge from hospital. Patients continue to recover function for the first 6 months postoperatively [70, 71]. Therefore, additional prognostic factors for longer-term functional outcomes may not have been captured by this review. We followed the recommendation from Hayden et al. for quality appraisal [24]. This resulted in assigning an overall level of evidence to just three factors. A more recent study by Hayden et al. recommends assigning overall low risk of bias if the ‘most important (determined as a priori)’ of the six bias domains are rated as having low risk [23]. This would have enabled us to assign a level of evidence to additional factors. However, ranking bias domains by importance may lead to reviewer bias. More recently, overall risk was assigned based on a count of low, moderate and high risk within a study [24]. This may result in a study being judged as low overall risk of bias even if two domains are high bias. Future research should identify the optimal approach for assigning overall risk of bias in prognostic systematic reviews. Conclusion We assigned two factors a weak evidence level—anaemia on admission and cognition. We assigned Parkinson’s disease an inconclusive evidence level. Future research may target these patients by intervening directly on the prognostic factor, or the proposed modifiable underlying mechanism. We identified an additional 22 prognostic factors of functional outcomes after hip fracture surgery. However, we could not assign an evidence level to any other factors due to the high bias identified during quality assessment. Further research is required to generate high-quality prognostic studies of additional factors of functional outcomes after hip fracture surgery and their underlying mechanisms. Key points Hip fracture leads to functional impairment, institutionalisation and death. Variation in outcomes of rehabilitation may result in part from differences between patients who undergo hip fracture surgery. The strongest prognostic factors for functional outcomes were cognitive impairment and anaemia. Potential to target these patients for intervention of intensive rehabilitation or more liberal transfusion strategy. Need for high-quality prognostic studies of additional factors of functional outcome after hip fracture surgery. Supplementary Data Supplementary data mentioned in the text are available to subscribers in Age and Ageing online. Conflict of interest None. Funding None. PROSPERO Registration Number CRD42017069148. 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Nurs Health Sci 2010 ; 12 : 336 – 44 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Age and Ageing Oxford University Press

Prognostic factors of functional outcome after hip fracture surgery: a systematic review

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com
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0002-0729
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1468-2834
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10.1093/ageing/afy057
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Abstract

Abstract Objective this systematic review aimed to identify immutable and modifiable prognostic factors of functional outcomes and their proposed mechanism after hip fracture surgery. Design systematic search of MEDLINE, Embase, CINAHL, PEDRO, OpenGrey and ClinicalTrials.gov for observational studies of prognostic factors of functional outcome after hip fracture among surgically treated adults with mean age of 65 years and older. Study selection, quality assessment, and data extraction were completed independently by two reviewers. The Quality in Prognosis Studies Tool was used for quality assessment and assigning a level of evidence to factors. Proposed mechanisms for reported associations were extracted from discussion sections. Results from 33 studies of 9,552 patients, we identified 25 prognostic factors of functional outcome after hip fracture surgery. We organised factors into groups: demographics, injury and comorbidities, body composition, complications, and acute care. We assigned two factors a weak evidence level—anaemia and cognition. We assigned Parkinson’s disease an inconclusive evidence level. We could not assign an evidence level to the remaining 22 factors due to the high risk of bias across studies. Frailty was the proposed mechanism for the association between anaemia and functional outcome. Medication management, perceived potential, complications and time to mobility were proposed as mechanisms for the association between cognition and functional outcome. Conclusion we identified one modifiable and one immutable prognostic factor for functional outcomes after hip fracture surgery. Future research may target patients with anaemia or cognitive impairment by intervening on the prognostic factor or the underlying mechanisms. hip fracture, functional recovery, prognosis, systematic review, older people Introduction In the UK, 75,000 men and women over the age of 60 years are admitted to acute care with hip fracture each year [1]. The injury has been dubbed the ‘hip attack’, due to its clinical severity and adverse consequences [2]. Even with treatment, up to 10% of patients die postoperatively in hospital [3]. Among survivors, 25% never recover their prefracture function, and 22% transition from independent living to long-term care [4–6]. Clinicians take steps to improve functional outcomes changing how patients are assessed and rehabilitated after hip fracture surgery [7–9]. Yet the most effective rehabilitation remains unclear [7–9]. This uncertainty may be due to limited understanding of the extent of prognostic factors [10, 11]. For example, studies suggest sex [12], fracture type [12], surgery type [13] and time to surgery [14] are associated with functional outcomes after hip fracture. Indeed, outcomes may vary between women treated early for transcervical fracture with arthroplasty and men treated late for intertrochanteric fracture with internal fixation. Uncertainty over the most effective rehabilitation may also be due to limited understanding of the nature of prognostic factors. Prognostic factors are immutable when interventions cannot change the factor level [15]. Knowledge of immutable prognostic factors would enable clinicians to adopt a stratified care approach by prioritising those at high risk of poor functional outcomes for more intensive rehabilitation [11]. In contrast, prognostic factors are modifiable when interventions may change the factor level [15]. Indeed, in the UK, Best Practice Tariffs target modifiable prognostic factors of mortality after hip fracture surgery for health care improvement [16] No attempt has been made to synthesise the extent and nature of prognostic factors for functional outcomes after hip fracture surgery. Therefore, we conducted a systematic review of the literature to identify both modifiable and immutable prognostic factors for functional outcomes of hip fracture surgery. We further summarised these factors on the proposed underlying mechanism for the reported associations. Methods Search strategy The protocol for this systematic review was registered on the International Register of Systematic Reviews (PROSPERO) (CRD42017069148) [17]. Databases were searched for published (MEDLINE, Embase, CINAHL and PEDRO) and unpublished (OpenGrey) studies and protocols (ClinicalTrials.gov) (see Appendix 1, Supplementary data are available in Age and Ageing online). The search was developed using terms for hip fracture and functional outcome employed by previous Cochrane Systematic Reviews [18–21]. Reference lists of retrieved studies were screened to identify additional studies that may have been missed during database searches. Authors were contacted for further information, if required. Selection criteria We exported citations from databases into Covidence for de-duplication and screening [22]. Two reviewers independently screened all abstracts against inclusion and exclusion criteria (R1, R2). Conflicts were resolved by a third reviewer (R3). Full texts of potentially eligible studies were independently screened by two reviewers (R2, R3) with conflicts resolved by a third reviewer (R1). Inclusion criteria We included observational studies which reported the association between a prognostic factor and any measure of functional outcome (function, mobility or balance) on discharge from acute care. We included observational studies of adults with mean age of 65 years and older who underwent surgery after non-pathological closed hip fracture, published in English between 1 January 2007 and 30 June 2017. Exclusion criteria We excluded studies of adults with mean age <65 years, admitted with an injury other than hip fracture, treated conservatively for hip fracture, treated surgically for a pathological or open hip fracture, or which reported on non-functional outcomes or outcomes following discharge. We excluded intervention-based studies on the premise they do not reflect prognostic factors of functional outcome following usual care, as well as case studies, editorials, commentaries and conference proceedings. Quality assessment Selected studies were assessed independently for methodological quality by two reviewers (R1, R2) using the Quality in Prognosis Studies (QUIPS) tool [23]. The QUIPS tool assesses risk of bias in six domains—participation, attrition, prognostic factor measurement, outcome measurement, confounding, and statistical analysis and reporting [23]. Conflicts were resolved by consensus (R1, R2). We assigned a level of evidence for each factor according to guidelines developed by Hayden et al. ‘that studies of acceptable quality for inclusion in the synthesis would at least partly satisfy each of the six biases (that is, studies from the analysis that are at high risk for any important bias would be omitted)’ [24]. This guideline was adapted for use with the QUIPS tool by Burton et al.[25] Studies were assigned an overall high risk of bias if one or more domains were considered high risk [24]. Studies were assigned a moderate risk of bias if three or more domains were moderate risk and none were high risk [24, 25]. Studies were assigned a low risk of bias if three or more domains were low risk and none were high risk [24, 25]. Data extraction Data extraction was completed by one reviewer onto tables designed a priori (R2). All data was checked for accuracy by a second reviewer (R1). Data extracted included the author’s name, publication date, study population, age, sample size, eligibility criteria, prognostic factor measurement, outcome measurement, length of stay, analysis type and effect estimate. The proposed mechanisms for reported associations were extracted from the discussion sections by one reviewer (R1). The extraction was checked for accuracy by a second reviewer (R3). Analysis We reported study characteristics as counts and proportions. We reviewed the data extraction tables to assess for study heterogeneity. There was variation in eligibility criteria, prognostic factor measurement, and outcome measurement across studies. Therefore, we analysed the association between prognostic factors and functional outcomes using a narrative review approach [26]. We summarised the evidence on prognostic factors and their underlying mechanisms in tables. We further summarised factors and their proposed mechanisms in a dependency graph to represent relationships among assembled factors [27]. We synthesised the evidence for prognostic factors where the overall risk of bias was low [24]. Results Study selection Figure 1 presents a flow diagram of study selection. We identified 3,487 studies after de-duplication. Following title and abstract screening 155 full-text studies progressed to full-text review. We subsequently included 33 studies in this review. Figure 1. View largeDownload slide Study selection. Figure 1. View largeDownload slide Study selection. Study characteristics This systematic review included 9,552 patients (mean age 68–89 years). Sample size ranged from 55 [28] to 1114 [29] patients (Table 1). Functional outcome was measured by Functional Independence Measure in 11 studies [29–39], Barthel index in eight studies [40–47], modified Barthel index in six studies [48–53], Tinetti [44, 54] and Timed Up and Go in two studies [28, 55], and Elderly Mobility Scale [56] and Cumulated Ambulation Score [30] in one study. Four studies developed their own functional outcome measure [57–60]. Length of stay after hip fracture surgery ranged from 1 [30] to 55 [36] days across studies. Table 1. Prognostic factors assessed for association with functional outcome after hip fracture surgery Author/year Risk of bias Sample size Prognostic factor Outcome LOS (days) Effect estimates(95% CI) Adam 2013 High 90 EMS EMS, LEFS NA 1.4 (CI NA) Adunksy 2008 High NA Anaemia on discharge FIM 32 0.8 (0.3–1.8) Adunksy 2011 High 606 Change in GFR FIM 31–32 1.0 (1.0–1.0) Adunksy 2015 High 707 Post-voiding residual volume FIM 30–31 −1.8 (−3.8 to −0.2) Adunksy 2012 High 1114 Atrial fibrillation FIM 29–33 NA Arinzon 2007 High 165 VAS FIM 42–55 −6.7 (−12.2 to −1.3) Benedetti 2015 High 249 SPMSQ BI 10 0.6 Bliemel 2015 Low 402 Parkinson’s disease BI, POMA, TUG 14–17 P = 0.1 Bliemel 2015B High 402 MMSE BI 12–15 −16.1 (−21.5 to −10.5) Buecking 2015 High 392 Age, BI, CCI, anaemia on admission, MMSE, time to surgery POMA NA Age: −0.2 (−0.3 to −0.1) BI: 0.1 (0.1–0.2) CCI: −0.4 (−0.8 to −0.0) Anaemia on admission: 0.1 (0.0–0.1) MMSE: 0.2 (0.1–0.4) Time to surgery: −0.1 (−0.1 to −0.0) Doshi 2014 High 179 Age MBI 10 P > 0.05 Dubljanin-Raspopovic 2011 Low 343 Anaemia on admission FIM 31 1.3 (1.0–1.3) Dubljanin Raspopovic 2014 High 112 GDS FIM 28 GDS −0.2 (−11.5 to 0.1) Enemark 2017 High 73 Parkinson’s disease Mobility* 12 P = 0.1 Goisser 2015 High 117 Dietary intake BI 13 P = 0·003 Goisser 2015 High 117 MNA BI 5–45 P = 0.2 Gonzalez-Montalvo 2016 High 479 Sarcopenia FAC, BI 10 1.7 (0.99–2.8) Horikawa 2014 High 99 Prefracture residence ADL† 34–49 P < 0.001 Hulsbaek 2015 High 167 Age, sex, NMS, procedure type, time to mobilisation, anaemia on discharge CAS 1–18 Age: 4.3 (1.8–10.1) Sex: 0.9 (0.4–2.4) NMS: 7.0 (2.9–17.0) Procedure type: 1.6 (0.7–3.9) Time to mobilisation: 3.3(1.3–8.0) Anaemia on discharge: 5.8 (CI: NA) Kondo 2010 High 211 LOS Mobility‡ 8–44 0.2 (0.0–0.9) Kristensen 2009 High 436 Age, NMS, fracture type TUG NA Age: 0.5 (0.2–0.8) NMS: −10.8 (−16.5 to −5.0) Fracture type: 6.6 (1.9–11.1) Kristensen 2013 High 55 VAS TUG NA VAS: 8.7 (2.1–15.2)¶ Lee 2013 High 293 DVT MBI BBS NA MBI P = 0.8 BBS P = 0.2 Lieberman 2007 High 224 Diabetes FIM 29–32 P = 0.001 Liu 2015 High 261 Vitamin D BI 10–33 5.2 (3.1–8.2) Martin-Martin 2015 High 186 Age, MBI, fracture type, GHQ-28, LOS POMA NA Age: −0.1 (−0.2 to 0.1) MBI: 0.1 (0.1–0.1) Fracture type: −1.5 (−2.8 to −0.2) GHQ-28: −0.2 (−0.3 to −0.1) LOS: −0.1 (−0.1 to −0.0) Mizrahi 2007 High 449 Albumin FIM 31–32 P = 0.4 Morghen 2011 High 386 MMSE MBI 28–29 NA Morghen 2011 High 423 GDS MBI 27–29 Mild 1.6 (0.8–3.3) Moderate/Severe 1.6 (1.3–7.8) Seng 2015 High 210 Vitamin D MBI NA NA Shakouri 2009 High 117 Age, FIM, BMI, LOS FIM NA NA LOS: P > 0.05 Uriz-Otano 2015 Low 285 Prefracture function, delirium, medications, pressure ulcers, urinary retention, MMSE BI 9–10 Prefracture function: 5.6 (2.4–12.7) Delirium: 3.2 (1.1–9.5) Medications: 1.6 (1.2–2.1) ** Pressure ulcers: 11.1 (2.9–43.3) Urinary retention: 3.9 (1.0–15.0) MMSE 1.1 (1.0–1.2) Yonezawa 2009 High 203 Time to surgery Mobility§ 38–40 P = 0.04 Author/year Risk of bias Sample size Prognostic factor Outcome LOS (days) Effect estimates(95% CI) Adam 2013 High 90 EMS EMS, LEFS NA 1.4 (CI NA) Adunksy 2008 High NA Anaemia on discharge FIM 32 0.8 (0.3–1.8) Adunksy 2011 High 606 Change in GFR FIM 31–32 1.0 (1.0–1.0) Adunksy 2015 High 707 Post-voiding residual volume FIM 30–31 −1.8 (−3.8 to −0.2) Adunksy 2012 High 1114 Atrial fibrillation FIM 29–33 NA Arinzon 2007 High 165 VAS FIM 42–55 −6.7 (−12.2 to −1.3) Benedetti 2015 High 249 SPMSQ BI 10 0.6 Bliemel 2015 Low 402 Parkinson’s disease BI, POMA, TUG 14–17 P = 0.1 Bliemel 2015B High 402 MMSE BI 12–15 −16.1 (−21.5 to −10.5) Buecking 2015 High 392 Age, BI, CCI, anaemia on admission, MMSE, time to surgery POMA NA Age: −0.2 (−0.3 to −0.1) BI: 0.1 (0.1–0.2) CCI: −0.4 (−0.8 to −0.0) Anaemia on admission: 0.1 (0.0–0.1) MMSE: 0.2 (0.1–0.4) Time to surgery: −0.1 (−0.1 to −0.0) Doshi 2014 High 179 Age MBI 10 P > 0.05 Dubljanin-Raspopovic 2011 Low 343 Anaemia on admission FIM 31 1.3 (1.0–1.3) Dubljanin Raspopovic 2014 High 112 GDS FIM 28 GDS −0.2 (−11.5 to 0.1) Enemark 2017 High 73 Parkinson’s disease Mobility* 12 P = 0.1 Goisser 2015 High 117 Dietary intake BI 13 P = 0·003 Goisser 2015 High 117 MNA BI 5–45 P = 0.2 Gonzalez-Montalvo 2016 High 479 Sarcopenia FAC, BI 10 1.7 (0.99–2.8) Horikawa 2014 High 99 Prefracture residence ADL† 34–49 P < 0.001 Hulsbaek 2015 High 167 Age, sex, NMS, procedure type, time to mobilisation, anaemia on discharge CAS 1–18 Age: 4.3 (1.8–10.1) Sex: 0.9 (0.4–2.4) NMS: 7.0 (2.9–17.0) Procedure type: 1.6 (0.7–3.9) Time to mobilisation: 3.3(1.3–8.0) Anaemia on discharge: 5.8 (CI: NA) Kondo 2010 High 211 LOS Mobility‡ 8–44 0.2 (0.0–0.9) Kristensen 2009 High 436 Age, NMS, fracture type TUG NA Age: 0.5 (0.2–0.8) NMS: −10.8 (−16.5 to −5.0) Fracture type: 6.6 (1.9–11.1) Kristensen 2013 High 55 VAS TUG NA VAS: 8.7 (2.1–15.2)¶ Lee 2013 High 293 DVT MBI BBS NA MBI P = 0.8 BBS P = 0.2 Lieberman 2007 High 224 Diabetes FIM 29–32 P = 0.001 Liu 2015 High 261 Vitamin D BI 10–33 5.2 (3.1–8.2) Martin-Martin 2015 High 186 Age, MBI, fracture type, GHQ-28, LOS POMA NA Age: −0.1 (−0.2 to 0.1) MBI: 0.1 (0.1–0.1) Fracture type: −1.5 (−2.8 to −0.2) GHQ-28: −0.2 (−0.3 to −0.1) LOS: −0.1 (−0.1 to −0.0) Mizrahi 2007 High 449 Albumin FIM 31–32 P = 0.4 Morghen 2011 High 386 MMSE MBI 28–29 NA Morghen 2011 High 423 GDS MBI 27–29 Mild 1.6 (0.8–3.3) Moderate/Severe 1.6 (1.3–7.8) Seng 2015 High 210 Vitamin D MBI NA NA Shakouri 2009 High 117 Age, FIM, BMI, LOS FIM NA NA LOS: P > 0.05 Uriz-Otano 2015 Low 285 Prefracture function, delirium, medications, pressure ulcers, urinary retention, MMSE BI 9–10 Prefracture function: 5.6 (2.4–12.7) Delirium: 3.2 (1.1–9.5) Medications: 1.6 (1.2–2.1) ** Pressure ulcers: 11.1 (2.9–43.3) Urinary retention: 3.9 (1.0–15.0) MMSE 1.1 (1.0–1.2) Yonezawa 2009 High 203 Time to surgery Mobility§ 38–40 P = 0.04 Abbreviations: EMS, Elderly Mobility Score; LEFS, Lower Extremity Functional Scale; BI, Barthel Index; MBI, Modified Barthel Index; NMS, New Mobility Score; CAS, Cumulated Ambulation Score; TUG, Timed Up and Go, Tinetti Performance Orientated Mobility Assessment; MMSE, mini mental state exam; SPMSQ, short portable mental status questionnaire; MNA, mini nutritional assessment; BMI, body mass index; FAC, Functional Ambulation Category; LOS, length of stay; FIM, Functional Independence Measure; NA, not available; CI, confidence interval. *Mobility = independent—able to walk using a walker or walking stick but without the assistance from another person. Patients able to walk before hip fracture but not at discharge from the hospital were described as having ‘loss of mobility’. †ADL—1–5 1= bed rest immobilisation for 24 h, 2 = use of wheelchair with caregiver’s aid, 3 = walking possible with a walking aid at home or in a geriatric health service facility, 4 = independent gait with a T-cane aid anytime and anywhere, 5 = independent gait with no aid during daily activities. ‡Mobility 1 = walk independent without the use of equipment, 2 = walk with cane, 3 = walk with a walking frame or cart, 4 = needs assistance, 5 = use of a wheelchair and 6 = confined to bed. §Mobility 1 = independently walking without cane, 2 = single cane walker or without cane but rather unstable, 3 = with a walker, walk while holding onto something or walk with support, 4 = move by wheelchair ¶from multivariate regression which did not include fracture type as a covariate. **Walking component of BI only. Table 1. Prognostic factors assessed for association with functional outcome after hip fracture surgery Author/year Risk of bias Sample size Prognostic factor Outcome LOS (days) Effect estimates(95% CI) Adam 2013 High 90 EMS EMS, LEFS NA 1.4 (CI NA) Adunksy 2008 High NA Anaemia on discharge FIM 32 0.8 (0.3–1.8) Adunksy 2011 High 606 Change in GFR FIM 31–32 1.0 (1.0–1.0) Adunksy 2015 High 707 Post-voiding residual volume FIM 30–31 −1.8 (−3.8 to −0.2) Adunksy 2012 High 1114 Atrial fibrillation FIM 29–33 NA Arinzon 2007 High 165 VAS FIM 42–55 −6.7 (−12.2 to −1.3) Benedetti 2015 High 249 SPMSQ BI 10 0.6 Bliemel 2015 Low 402 Parkinson’s disease BI, POMA, TUG 14–17 P = 0.1 Bliemel 2015B High 402 MMSE BI 12–15 −16.1 (−21.5 to −10.5) Buecking 2015 High 392 Age, BI, CCI, anaemia on admission, MMSE, time to surgery POMA NA Age: −0.2 (−0.3 to −0.1) BI: 0.1 (0.1–0.2) CCI: −0.4 (−0.8 to −0.0) Anaemia on admission: 0.1 (0.0–0.1) MMSE: 0.2 (0.1–0.4) Time to surgery: −0.1 (−0.1 to −0.0) Doshi 2014 High 179 Age MBI 10 P > 0.05 Dubljanin-Raspopovic 2011 Low 343 Anaemia on admission FIM 31 1.3 (1.0–1.3) Dubljanin Raspopovic 2014 High 112 GDS FIM 28 GDS −0.2 (−11.5 to 0.1) Enemark 2017 High 73 Parkinson’s disease Mobility* 12 P = 0.1 Goisser 2015 High 117 Dietary intake BI 13 P = 0·003 Goisser 2015 High 117 MNA BI 5–45 P = 0.2 Gonzalez-Montalvo 2016 High 479 Sarcopenia FAC, BI 10 1.7 (0.99–2.8) Horikawa 2014 High 99 Prefracture residence ADL† 34–49 P < 0.001 Hulsbaek 2015 High 167 Age, sex, NMS, procedure type, time to mobilisation, anaemia on discharge CAS 1–18 Age: 4.3 (1.8–10.1) Sex: 0.9 (0.4–2.4) NMS: 7.0 (2.9–17.0) Procedure type: 1.6 (0.7–3.9) Time to mobilisation: 3.3(1.3–8.0) Anaemia on discharge: 5.8 (CI: NA) Kondo 2010 High 211 LOS Mobility‡ 8–44 0.2 (0.0–0.9) Kristensen 2009 High 436 Age, NMS, fracture type TUG NA Age: 0.5 (0.2–0.8) NMS: −10.8 (−16.5 to −5.0) Fracture type: 6.6 (1.9–11.1) Kristensen 2013 High 55 VAS TUG NA VAS: 8.7 (2.1–15.2)¶ Lee 2013 High 293 DVT MBI BBS NA MBI P = 0.8 BBS P = 0.2 Lieberman 2007 High 224 Diabetes FIM 29–32 P = 0.001 Liu 2015 High 261 Vitamin D BI 10–33 5.2 (3.1–8.2) Martin-Martin 2015 High 186 Age, MBI, fracture type, GHQ-28, LOS POMA NA Age: −0.1 (−0.2 to 0.1) MBI: 0.1 (0.1–0.1) Fracture type: −1.5 (−2.8 to −0.2) GHQ-28: −0.2 (−0.3 to −0.1) LOS: −0.1 (−0.1 to −0.0) Mizrahi 2007 High 449 Albumin FIM 31–32 P = 0.4 Morghen 2011 High 386 MMSE MBI 28–29 NA Morghen 2011 High 423 GDS MBI 27–29 Mild 1.6 (0.8–3.3) Moderate/Severe 1.6 (1.3–7.8) Seng 2015 High 210 Vitamin D MBI NA NA Shakouri 2009 High 117 Age, FIM, BMI, LOS FIM NA NA LOS: P > 0.05 Uriz-Otano 2015 Low 285 Prefracture function, delirium, medications, pressure ulcers, urinary retention, MMSE BI 9–10 Prefracture function: 5.6 (2.4–12.7) Delirium: 3.2 (1.1–9.5) Medications: 1.6 (1.2–2.1) ** Pressure ulcers: 11.1 (2.9–43.3) Urinary retention: 3.9 (1.0–15.0) MMSE 1.1 (1.0–1.2) Yonezawa 2009 High 203 Time to surgery Mobility§ 38–40 P = 0.04 Author/year Risk of bias Sample size Prognostic factor Outcome LOS (days) Effect estimates(95% CI) Adam 2013 High 90 EMS EMS, LEFS NA 1.4 (CI NA) Adunksy 2008 High NA Anaemia on discharge FIM 32 0.8 (0.3–1.8) Adunksy 2011 High 606 Change in GFR FIM 31–32 1.0 (1.0–1.0) Adunksy 2015 High 707 Post-voiding residual volume FIM 30–31 −1.8 (−3.8 to −0.2) Adunksy 2012 High 1114 Atrial fibrillation FIM 29–33 NA Arinzon 2007 High 165 VAS FIM 42–55 −6.7 (−12.2 to −1.3) Benedetti 2015 High 249 SPMSQ BI 10 0.6 Bliemel 2015 Low 402 Parkinson’s disease BI, POMA, TUG 14–17 P = 0.1 Bliemel 2015B High 402 MMSE BI 12–15 −16.1 (−21.5 to −10.5) Buecking 2015 High 392 Age, BI, CCI, anaemia on admission, MMSE, time to surgery POMA NA Age: −0.2 (−0.3 to −0.1) BI: 0.1 (0.1–0.2) CCI: −0.4 (−0.8 to −0.0) Anaemia on admission: 0.1 (0.0–0.1) MMSE: 0.2 (0.1–0.4) Time to surgery: −0.1 (−0.1 to −0.0) Doshi 2014 High 179 Age MBI 10 P > 0.05 Dubljanin-Raspopovic 2011 Low 343 Anaemia on admission FIM 31 1.3 (1.0–1.3) Dubljanin Raspopovic 2014 High 112 GDS FIM 28 GDS −0.2 (−11.5 to 0.1) Enemark 2017 High 73 Parkinson’s disease Mobility* 12 P = 0.1 Goisser 2015 High 117 Dietary intake BI 13 P = 0·003 Goisser 2015 High 117 MNA BI 5–45 P = 0.2 Gonzalez-Montalvo 2016 High 479 Sarcopenia FAC, BI 10 1.7 (0.99–2.8) Horikawa 2014 High 99 Prefracture residence ADL† 34–49 P < 0.001 Hulsbaek 2015 High 167 Age, sex, NMS, procedure type, time to mobilisation, anaemia on discharge CAS 1–18 Age: 4.3 (1.8–10.1) Sex: 0.9 (0.4–2.4) NMS: 7.0 (2.9–17.0) Procedure type: 1.6 (0.7–3.9) Time to mobilisation: 3.3(1.3–8.0) Anaemia on discharge: 5.8 (CI: NA) Kondo 2010 High 211 LOS Mobility‡ 8–44 0.2 (0.0–0.9) Kristensen 2009 High 436 Age, NMS, fracture type TUG NA Age: 0.5 (0.2–0.8) NMS: −10.8 (−16.5 to −5.0) Fracture type: 6.6 (1.9–11.1) Kristensen 2013 High 55 VAS TUG NA VAS: 8.7 (2.1–15.2)¶ Lee 2013 High 293 DVT MBI BBS NA MBI P = 0.8 BBS P = 0.2 Lieberman 2007 High 224 Diabetes FIM 29–32 P = 0.001 Liu 2015 High 261 Vitamin D BI 10–33 5.2 (3.1–8.2) Martin-Martin 2015 High 186 Age, MBI, fracture type, GHQ-28, LOS POMA NA Age: −0.1 (−0.2 to 0.1) MBI: 0.1 (0.1–0.1) Fracture type: −1.5 (−2.8 to −0.2) GHQ-28: −0.2 (−0.3 to −0.1) LOS: −0.1 (−0.1 to −0.0) Mizrahi 2007 High 449 Albumin FIM 31–32 P = 0.4 Morghen 2011 High 386 MMSE MBI 28–29 NA Morghen 2011 High 423 GDS MBI 27–29 Mild 1.6 (0.8–3.3) Moderate/Severe 1.6 (1.3–7.8) Seng 2015 High 210 Vitamin D MBI NA NA Shakouri 2009 High 117 Age, FIM, BMI, LOS FIM NA NA LOS: P > 0.05 Uriz-Otano 2015 Low 285 Prefracture function, delirium, medications, pressure ulcers, urinary retention, MMSE BI 9–10 Prefracture function: 5.6 (2.4–12.7) Delirium: 3.2 (1.1–9.5) Medications: 1.6 (1.2–2.1) ** Pressure ulcers: 11.1 (2.9–43.3) Urinary retention: 3.9 (1.0–15.0) MMSE 1.1 (1.0–1.2) Yonezawa 2009 High 203 Time to surgery Mobility§ 38–40 P = 0.04 Abbreviations: EMS, Elderly Mobility Score; LEFS, Lower Extremity Functional Scale; BI, Barthel Index; MBI, Modified Barthel Index; NMS, New Mobility Score; CAS, Cumulated Ambulation Score; TUG, Timed Up and Go, Tinetti Performance Orientated Mobility Assessment; MMSE, mini mental state exam; SPMSQ, short portable mental status questionnaire; MNA, mini nutritional assessment; BMI, body mass index; FAC, Functional Ambulation Category; LOS, length of stay; FIM, Functional Independence Measure; NA, not available; CI, confidence interval. *Mobility = independent—able to walk using a walker or walking stick but without the assistance from another person. Patients able to walk before hip fracture but not at discharge from the hospital were described as having ‘loss of mobility’. †ADL—1–5 1= bed rest immobilisation for 24 h, 2 = use of wheelchair with caregiver’s aid, 3 = walking possible with a walking aid at home or in a geriatric health service facility, 4 = independent gait with a T-cane aid anytime and anywhere, 5 = independent gait with no aid during daily activities. ‡Mobility 1 = walk independent without the use of equipment, 2 = walk with cane, 3 = walk with a walking frame or cart, 4 = needs assistance, 5 = use of a wheelchair and 6 = confined to bed. §Mobility 1 = independently walking without cane, 2 = single cane walker or without cane but rather unstable, 3 = with a walker, walk while holding onto something or walk with support, 4 = move by wheelchair ¶from multivariate regression which did not include fracture type as a covariate. **Walking component of BI only. Quality assessment The results of the quality assessment are presented in Appendix 2, Supplementary data are available in Age and Ageing online. The agreement between two independent reviewers regarding the risk of bias domains was 90%. Following discussion 100% consensus was reached. In total, three studies (9%) had low overall risk of bias [33, 42, 44] and 30 studies (91%) had high overall risk of bias [28–32, 34–41, 43, 45–60]. The main reasons for high bias assignment were study confounding, participation, and attrition. Failure to control for important potential confounders (e.g. prefracture function, comorbidity) was a high risk of bias in 13 studies (39%) [30, 31, 35, 40, 43, 48, 50–54, 57, 59]. Overall, nine studies (27%) did not adjust for any potential confounders [30, 31, 40, 43, 51, 52, 57–59]. For 21 studies (64%) participant eligibility criteria were narrow [28, 30–32, 34–39, 45–50, 52, 53, 55, 59, 60]. In particular, eight studies (24%) excluded patients with cognitive impairment [31, 36–38, 48, 49, 51, 53]. Additional detail on participant exclusions may be found in Appendices 3–8, Supplementary data are available in Age and Ageing online. A total of six studies (18%) failed to provide reasons for loss to follow-up, or a comparison between those lost to follow-up and those observed for the study duration [41, 48, 50, 51, 55, 60]. Prognostic factors Overall, 25 prognostic factors of functional outcome after hip fracture surgery were identified by 33 studies (Table 1). Three factors were reported by studies with low overall risk of bias. We assigned a weak level of evidence for an association between functional outcome and cognitive impairment [42], and between functional outcome and anaemia on admission [33]. We assigned an inconclusive level of evidence for an association between functional outcome and Parkinson’s disease [44]. Prefracture function [42, 49], perceived potential [49], medication management [42], complications [42] and time to mobilisation [30] were proposed as underlying mechanisms for the association between cognitive impairment and functional outcome. Frailty and weakness were proposed as underlying mechanisms for the association between anaemia on admission and functional outcome [33]. Medication management and complications were proposed as underlying mechanisms for the association between Parkinson’s disease and functional outcome (Table 2 and Figure 2) [58]. Table 2. Proposed mechanisms and mediators for the functional outcome effect of prognostic factors Factor Mechanism Mediator Age Functional impairment increases with age [52]. Prefracture function Cognitive impairment increases with age [42]. Cognitive impairment Pain scores decrease with age. Older patients may be more likely to accept the pain medication provided by their health professionals is appropriate than younger patients [28]. Pain Sex Women more often present with depression than men [37]. Depression For women, urinary retention is associated with functional outcome [35]. Urinary retention Women with hip fracture are older than men [37]. Age Women present with more comorbidities than men [37]. Comorbidity count Women present with more cognitive impairment than men [37]. Cognitive impairment Prefracture residence Patients admitted from long-term care present with more cognitive impairment than those admitted from home [59]. Cognitive impairment Patients admitted from long-term care present with more comorbidities than those from home [53]. Comorbidity count Patients admitted from long-term care develop more complications than those from home [53]. Complications Patients admitted from long-term care are less likely to undergo early mobilisation than those from home [53, 59]. Time to mobilisation Comorbidity count Cognitive impairment increases with comorbidity count [42]. Cognitive impairment Length of stay increases with comorbidity count [53]. Length of stay Patients with more comorbidities are less likely to undergo early mobilisation than those with less comorbidities [30]. Time to mobilisation Diabetes Patients with diabetes are more likely to develop postoperative urinary retention than those without diabetes [35]. Complications Patients with diabetes are more likely to present with history of stroke than those without diabetes [38]. Stroke history Patients with diabetes present with less prefracture function than those without diabetes [38]. Prefracture function Cognitive impairment For patients with cognitive impairment, prefracture function is associated with functional outcome [42, 49]. Prefracture function Patients with cognitive impairment may be seen to have less potential and therapists may reduce the intensity of rehabilitation compared to patients without cognitive impairment [49]. Perceived potential Patients with cognitive impairment present on more medications than those without cognitive impairment [42]. Medication management Patients with cognitive impairment develop more complications than those without cognitive impairment [42]. Complications Patients with cognitive impairment are less likely to mobilise early than those without cognitive impairment [30]. Time to mobilisation Vitamin D Skeletal muscles require vitamin D for structural maintenance and optimal function, with deficiency causing loss of muscle mass, atrophy of type II muscle fibres and weakness [47]. Weakness Parkinson’s Disease Patients with Parkinson’s disease may not receive medication on time with some omitted completely [58]. Medication management Patients with Parkinson’s disease develop more complications than those without Parkinson’s disease [58]. Complications Dehydration Increased urea production may reflect dehydration due to bleeding around the fracture site [34]. Blood urea Malnutrition Increased urea production is associated with malnutrition [34]. Blood urea Patients with malnourishment have more comorbidities than well-nourished patients [45]. Comorbidities Patients with malnourishment are more likely to have cognitive impairment than well-nourished patients [45]. Cognitive impairment Patients with malnourishment develop more complications than well-nourished patients [46]. Complications Patients with malnourishment are more likely to be frail than well-nourished patients[46]. Frailty Depression Patients with depression may be less likely to comply with rehabilitation than those without depression [36, 48, 54]. Adherence For patients with depression, pain is associated with functional outcome [36]. Pain Patients with depression are more likely to be frail than patients without depression [37]. Frailty Therapists reduce rehabilitation intensity more for patients with depression than those without depression [37, 48]. Perceived potential Fracture type Patients with a trochanteric hip fracture require more pain medication than those with femoral neck fractures [28]. Pain Patients with more severe fractures are less likely to mobilise early than those with less severe fractures [30]. Time to mobilisation Anaemia on admission Patients with low haemoglobin on admission are more likely to be frail than those with higher haemoglobin [33]. Frailty Patients with low haemoglobin on admission may have less strength than those with higher haemoglobin [33]. Weakness Time to surgery Patients with longer time to surgery have a longer time to mobilisation than those with shorter time to surgery [54]. Time to mobilisation Complications Patients with complications have a longer acute hospital stay than those without complications [53]. Length of stay Patients with complications wait longer before mobilising than those without complications [53]. Time to mobilisation Pain Patients with pain are less likely to adhere to rehabilitation than those without pain [36]. Adherence Patients with pain are less likely to undergo early mobilisation than those without pain [30]. Time to mobilisation Patients with pain are more likely to have disturbed sleep, appetite loss, and fatigue than those without pain [36]. Fatigue Patients who report pain are less likely to be cognitively impaired than those who do not report pain [36]. Cognitive impairment Factor Mechanism Mediator Age Functional impairment increases with age [52]. Prefracture function Cognitive impairment increases with age [42]. Cognitive impairment Pain scores decrease with age. Older patients may be more likely to accept the pain medication provided by their health professionals is appropriate than younger patients [28]. Pain Sex Women more often present with depression than men [37]. Depression For women, urinary retention is associated with functional outcome [35]. Urinary retention Women with hip fracture are older than men [37]. Age Women present with more comorbidities than men [37]. Comorbidity count Women present with more cognitive impairment than men [37]. Cognitive impairment Prefracture residence Patients admitted from long-term care present with more cognitive impairment than those admitted from home [59]. Cognitive impairment Patients admitted from long-term care present with more comorbidities than those from home [53]. Comorbidity count Patients admitted from long-term care develop more complications than those from home [53]. Complications Patients admitted from long-term care are less likely to undergo early mobilisation than those from home [53, 59]. Time to mobilisation Comorbidity count Cognitive impairment increases with comorbidity count [42]. Cognitive impairment Length of stay increases with comorbidity count [53]. Length of stay Patients with more comorbidities are less likely to undergo early mobilisation than those with less comorbidities [30]. Time to mobilisation Diabetes Patients with diabetes are more likely to develop postoperative urinary retention than those without diabetes [35]. Complications Patients with diabetes are more likely to present with history of stroke than those without diabetes [38]. Stroke history Patients with diabetes present with less prefracture function than those without diabetes [38]. Prefracture function Cognitive impairment For patients with cognitive impairment, prefracture function is associated with functional outcome [42, 49]. Prefracture function Patients with cognitive impairment may be seen to have less potential and therapists may reduce the intensity of rehabilitation compared to patients without cognitive impairment [49]. Perceived potential Patients with cognitive impairment present on more medications than those without cognitive impairment [42]. Medication management Patients with cognitive impairment develop more complications than those without cognitive impairment [42]. Complications Patients with cognitive impairment are less likely to mobilise early than those without cognitive impairment [30]. Time to mobilisation Vitamin D Skeletal muscles require vitamin D for structural maintenance and optimal function, with deficiency causing loss of muscle mass, atrophy of type II muscle fibres and weakness [47]. Weakness Parkinson’s Disease Patients with Parkinson’s disease may not receive medication on time with some omitted completely [58]. Medication management Patients with Parkinson’s disease develop more complications than those without Parkinson’s disease [58]. Complications Dehydration Increased urea production may reflect dehydration due to bleeding around the fracture site [34]. Blood urea Malnutrition Increased urea production is associated with malnutrition [34]. Blood urea Patients with malnourishment have more comorbidities than well-nourished patients [45]. Comorbidities Patients with malnourishment are more likely to have cognitive impairment than well-nourished patients [45]. Cognitive impairment Patients with malnourishment develop more complications than well-nourished patients [46]. Complications Patients with malnourishment are more likely to be frail than well-nourished patients[46]. Frailty Depression Patients with depression may be less likely to comply with rehabilitation than those without depression [36, 48, 54]. Adherence For patients with depression, pain is associated with functional outcome [36]. Pain Patients with depression are more likely to be frail than patients without depression [37]. Frailty Therapists reduce rehabilitation intensity more for patients with depression than those without depression [37, 48]. Perceived potential Fracture type Patients with a trochanteric hip fracture require more pain medication than those with femoral neck fractures [28]. Pain Patients with more severe fractures are less likely to mobilise early than those with less severe fractures [30]. Time to mobilisation Anaemia on admission Patients with low haemoglobin on admission are more likely to be frail than those with higher haemoglobin [33]. Frailty Patients with low haemoglobin on admission may have less strength than those with higher haemoglobin [33]. Weakness Time to surgery Patients with longer time to surgery have a longer time to mobilisation than those with shorter time to surgery [54]. Time to mobilisation Complications Patients with complications have a longer acute hospital stay than those without complications [53]. Length of stay Patients with complications wait longer before mobilising than those without complications [53]. Time to mobilisation Pain Patients with pain are less likely to adhere to rehabilitation than those without pain [36]. Adherence Patients with pain are less likely to undergo early mobilisation than those without pain [30]. Time to mobilisation Patients with pain are more likely to have disturbed sleep, appetite loss, and fatigue than those without pain [36]. Fatigue Patients who report pain are less likely to be cognitively impaired than those who do not report pain [36]. Cognitive impairment Table 2. Proposed mechanisms and mediators for the functional outcome effect of prognostic factors Factor Mechanism Mediator Age Functional impairment increases with age [52]. Prefracture function Cognitive impairment increases with age [42]. Cognitive impairment Pain scores decrease with age. Older patients may be more likely to accept the pain medication provided by their health professionals is appropriate than younger patients [28]. Pain Sex Women more often present with depression than men [37]. Depression For women, urinary retention is associated with functional outcome [35]. Urinary retention Women with hip fracture are older than men [37]. Age Women present with more comorbidities than men [37]. Comorbidity count Women present with more cognitive impairment than men [37]. Cognitive impairment Prefracture residence Patients admitted from long-term care present with more cognitive impairment than those admitted from home [59]. Cognitive impairment Patients admitted from long-term care present with more comorbidities than those from home [53]. Comorbidity count Patients admitted from long-term care develop more complications than those from home [53]. Complications Patients admitted from long-term care are less likely to undergo early mobilisation than those from home [53, 59]. Time to mobilisation Comorbidity count Cognitive impairment increases with comorbidity count [42]. Cognitive impairment Length of stay increases with comorbidity count [53]. Length of stay Patients with more comorbidities are less likely to undergo early mobilisation than those with less comorbidities [30]. Time to mobilisation Diabetes Patients with diabetes are more likely to develop postoperative urinary retention than those without diabetes [35]. Complications Patients with diabetes are more likely to present with history of stroke than those without diabetes [38]. Stroke history Patients with diabetes present with less prefracture function than those without diabetes [38]. Prefracture function Cognitive impairment For patients with cognitive impairment, prefracture function is associated with functional outcome [42, 49]. Prefracture function Patients with cognitive impairment may be seen to have less potential and therapists may reduce the intensity of rehabilitation compared to patients without cognitive impairment [49]. Perceived potential Patients with cognitive impairment present on more medications than those without cognitive impairment [42]. Medication management Patients with cognitive impairment develop more complications than those without cognitive impairment [42]. Complications Patients with cognitive impairment are less likely to mobilise early than those without cognitive impairment [30]. Time to mobilisation Vitamin D Skeletal muscles require vitamin D for structural maintenance and optimal function, with deficiency causing loss of muscle mass, atrophy of type II muscle fibres and weakness [47]. Weakness Parkinson’s Disease Patients with Parkinson’s disease may not receive medication on time with some omitted completely [58]. Medication management Patients with Parkinson’s disease develop more complications than those without Parkinson’s disease [58]. Complications Dehydration Increased urea production may reflect dehydration due to bleeding around the fracture site [34]. Blood urea Malnutrition Increased urea production is associated with malnutrition [34]. Blood urea Patients with malnourishment have more comorbidities than well-nourished patients [45]. Comorbidities Patients with malnourishment are more likely to have cognitive impairment than well-nourished patients [45]. Cognitive impairment Patients with malnourishment develop more complications than well-nourished patients [46]. Complications Patients with malnourishment are more likely to be frail than well-nourished patients[46]. Frailty Depression Patients with depression may be less likely to comply with rehabilitation than those without depression [36, 48, 54]. Adherence For patients with depression, pain is associated with functional outcome [36]. Pain Patients with depression are more likely to be frail than patients without depression [37]. Frailty Therapists reduce rehabilitation intensity more for patients with depression than those without depression [37, 48]. Perceived potential Fracture type Patients with a trochanteric hip fracture require more pain medication than those with femoral neck fractures [28]. Pain Patients with more severe fractures are less likely to mobilise early than those with less severe fractures [30]. Time to mobilisation Anaemia on admission Patients with low haemoglobin on admission are more likely to be frail than those with higher haemoglobin [33]. Frailty Patients with low haemoglobin on admission may have less strength than those with higher haemoglobin [33]. Weakness Time to surgery Patients with longer time to surgery have a longer time to mobilisation than those with shorter time to surgery [54]. Time to mobilisation Complications Patients with complications have a longer acute hospital stay than those without complications [53]. Length of stay Patients with complications wait longer before mobilising than those without complications [53]. Time to mobilisation Pain Patients with pain are less likely to adhere to rehabilitation than those without pain [36]. Adherence Patients with pain are less likely to undergo early mobilisation than those without pain [30]. Time to mobilisation Patients with pain are more likely to have disturbed sleep, appetite loss, and fatigue than those without pain [36]. Fatigue Patients who report pain are less likely to be cognitively impaired than those who do not report pain [36]. Cognitive impairment Factor Mechanism Mediator Age Functional impairment increases with age [52]. Prefracture function Cognitive impairment increases with age [42]. Cognitive impairment Pain scores decrease with age. Older patients may be more likely to accept the pain medication provided by their health professionals is appropriate than younger patients [28]. Pain Sex Women more often present with depression than men [37]. Depression For women, urinary retention is associated with functional outcome [35]. Urinary retention Women with hip fracture are older than men [37]. Age Women present with more comorbidities than men [37]. Comorbidity count Women present with more cognitive impairment than men [37]. Cognitive impairment Prefracture residence Patients admitted from long-term care present with more cognitive impairment than those admitted from home [59]. Cognitive impairment Patients admitted from long-term care present with more comorbidities than those from home [53]. Comorbidity count Patients admitted from long-term care develop more complications than those from home [53]. Complications Patients admitted from long-term care are less likely to undergo early mobilisation than those from home [53, 59]. Time to mobilisation Comorbidity count Cognitive impairment increases with comorbidity count [42]. Cognitive impairment Length of stay increases with comorbidity count [53]. Length of stay Patients with more comorbidities are less likely to undergo early mobilisation than those with less comorbidities [30]. Time to mobilisation Diabetes Patients with diabetes are more likely to develop postoperative urinary retention than those without diabetes [35]. Complications Patients with diabetes are more likely to present with history of stroke than those without diabetes [38]. Stroke history Patients with diabetes present with less prefracture function than those without diabetes [38]. Prefracture function Cognitive impairment For patients with cognitive impairment, prefracture function is associated with functional outcome [42, 49]. Prefracture function Patients with cognitive impairment may be seen to have less potential and therapists may reduce the intensity of rehabilitation compared to patients without cognitive impairment [49]. Perceived potential Patients with cognitive impairment present on more medications than those without cognitive impairment [42]. Medication management Patients with cognitive impairment develop more complications than those without cognitive impairment [42]. Complications Patients with cognitive impairment are less likely to mobilise early than those without cognitive impairment [30]. Time to mobilisation Vitamin D Skeletal muscles require vitamin D for structural maintenance and optimal function, with deficiency causing loss of muscle mass, atrophy of type II muscle fibres and weakness [47]. Weakness Parkinson’s Disease Patients with Parkinson’s disease may not receive medication on time with some omitted completely [58]. Medication management Patients with Parkinson’s disease develop more complications than those without Parkinson’s disease [58]. Complications Dehydration Increased urea production may reflect dehydration due to bleeding around the fracture site [34]. Blood urea Malnutrition Increased urea production is associated with malnutrition [34]. Blood urea Patients with malnourishment have more comorbidities than well-nourished patients [45]. Comorbidities Patients with malnourishment are more likely to have cognitive impairment than well-nourished patients [45]. Cognitive impairment Patients with malnourishment develop more complications than well-nourished patients [46]. Complications Patients with malnourishment are more likely to be frail than well-nourished patients[46]. Frailty Depression Patients with depression may be less likely to comply with rehabilitation than those without depression [36, 48, 54]. Adherence For patients with depression, pain is associated with functional outcome [36]. Pain Patients with depression are more likely to be frail than patients without depression [37]. Frailty Therapists reduce rehabilitation intensity more for patients with depression than those without depression [37, 48]. Perceived potential Fracture type Patients with a trochanteric hip fracture require more pain medication than those with femoral neck fractures [28]. Pain Patients with more severe fractures are less likely to mobilise early than those with less severe fractures [30]. Time to mobilisation Anaemia on admission Patients with low haemoglobin on admission are more likely to be frail than those with higher haemoglobin [33]. Frailty Patients with low haemoglobin on admission may have less strength than those with higher haemoglobin [33]. Weakness Time to surgery Patients with longer time to surgery have a longer time to mobilisation than those with shorter time to surgery [54]. Time to mobilisation Complications Patients with complications have a longer acute hospital stay than those without complications [53]. Length of stay Patients with complications wait longer before mobilising than those without complications [53]. Time to mobilisation Pain Patients with pain are less likely to adhere to rehabilitation than those without pain [36]. Adherence Patients with pain are less likely to undergo early mobilisation than those without pain [30]. Time to mobilisation Patients with pain are more likely to have disturbed sleep, appetite loss, and fatigue than those without pain [36]. Fatigue Patients who report pain are less likely to be cognitively impaired than those who do not report pain [36]. Cognitive impairment Figure 2. View largeDownload slide Prognostic factors and their proposed underling mechanisms for their association with functional outcome after hip fracture surgery. Nodes represent factors and their underlying mechanisms while arrows represent dependencies between nodes. Figure 2. View largeDownload slide Prognostic factors and their proposed underling mechanisms for their association with functional outcome after hip fracture surgery. Nodes represent factors and their underlying mechanisms while arrows represent dependencies between nodes. We organised the remaining 22 factors reported by studies of high risk of bias into five groups: demographics, injury and comorbidities, body composition, complications and acute care factors. A total of 38 potential underlying mechanisms were proposed for 14 factors (Table 2 and Figure 2). Demographics: Age [30, 31, 53–55], sex [30] and prefracture residence [59] were associated with functional outcome. Age [52] and sex [55] were also reported as not associated with functional outcome. Prefracture function [52], cognitive impairment [42], and pain [28] were proposed as underlying mechanism for the association between age and functional outcome. Depression [37], urinary retention [35], age [37], comorbidity [37] and cognitive impairment [37] were proposed as underlying mechanisms for the association between sex and functional outcome. Cognitive impairment [59], comorbidity [53], complications [53] and time to mobilisation [53, 59] were proposed as underlying mechanisms for the association between prefracture residence and functional outcome (Table 2 and Figure 2). Injury and comorbidities: Fracture type was associated with functional outcome after hip fracture surgery [53, 55]. Comorbidity as measured by Charlson Comorbidity Index was associated with functional outcome after hip fracture surgery [54]. Prefracture function [30, 31, 42, 53–56], diabetes [38], atrial fibrillation [29] and vitamin D level [47] were associated with poor functional outcome after hip fracture surgery. Polypharmacy was also associated with functional outcome [42]. Vitamin D level [50] was also reported as not associated with functional outcome. Pain [28] and time to mobilisation [30] were proposed as underlying mechanisms for the association between fracture type and functional outcome. Prefracture function [38], history of stroke [38] and complications [35] were proposed as underlying mechanisms for the association between diabetes and functional outcome. Weakness was the proposed underlying mechanism for the association between vitamin D and functional outcome (Table 2 and Figure 2) [47]. Body composition body mass index [31] and malnutrition [45, 46], were associated with functional outcome after hip fracture surgery. Sarcopenia was not associated with postoperative functional outcome [43]. Comorbidity [45], cognitive impairment [45], complications [46] and frailty [46] were proposed as underlying mechanisms for the association between malnutrition and functional outcome (Table 2 and Figure 2). Complications pain [36, 55], elevated blood urea [34, 35], perioperative urinary retention [34, 35, 42], pressure ulcers [42] and delirium [42] were associated with functional outcome. Emotional distress [53] and new onset depression [37, 49] were associated with functional outcome after hip fracture surgery. Deep vein thrombosis and anaemia on discharge [30, 32] were not associated with functional outcome [51]. Admission albumin level was not associated with functional outcome [39]. Pain [36], frailty [37], perceived rehabilitation potential [37, 48] and rehabilitation adherence [36, 48, 54] were proposed as underlying mechanisms for the association between new onset depression and functional outcome. Fatigue [36], cognitive impairment [36], time to mobilisation [30] and rehabilitation adherence [36] were proposed as underlying mechanisms for the association between pain and functional outcome. Malnutrition and dehydration were proposed as underlying mechanisms for the association between blood urea and functional outcome (Table 2 and Figure 2) [34]. Acute care factors Time to surgery [54, 57], time to mobilisation [30] and overall length of stay [53, 60] were associated with functional outcome. Length of stay [31] and procedure type [30] were also reported as not associated with functional outcome. Time to mobilisation was the proposed underlying mechanism for the association between time to surgery and functional outcome (Table 2 and Figure 2) [54]. Discussion We identified 25 prognostic factors of functional outcome after hip fracture surgery from 33 studies. We organised these factors into five groups; demographics, injury and comorbidities, body composition, complications and acute care factors. Overall, the risk of bias across studies was high. There was sufficient quality evidence to assign a weak level of evidence for anaemia on admission and cognitive impairment, and an inconclusive level of evidence for Parkinson’s disease. There was insufficient quality evidence to assign a level of evidence for the remaining 22 prognostic factors. Most studies included in this review focused on immutable factors of functional outcome after hip fracture surgery. Knowledge of these factors enables clinicians to adopt a stratified care approach by prioritising those at high risk of poor outcome [11]. We assigned a weak level of evidence for an association between cognitive impairment and functional outcome. A recent systematic review reported a positive association between rehabilitation and functional outcome after hip fracture surgery among patients with cognitive impairment [61]. Despite this cognitively impaired patients are often excluded from trials of new interventions [62]. While the presence of cognitive impairment may be considered an immutable factor [63], all four proposed underlying mechanisms are modifiable—medication management, perceived potential, occurrence of complications and time to mobilisation. Future high-quality prognostic studies are required to confirm or refute the proposed underlying mechanism for the reported association. Less studies focused on modifiable factors of functional outcomes after hip fracture surgery. To inform future Best Practice Tariffs there is a need for greater understanding of modifiable prognostic factors of functional outcomes such as rehabilitation access or staffing levels. We assigned a weak level of evidence for an association between anaemia on admission and functional outcome. However, a recent randomised controlled trial indicated that a more liberal blood transfusion policy did not lead to better recovery of activities of daily living than a more restrictive blood transfusion policy [64]. In the current review frailty and weakness (a feature of frailty) were proposed as underlying mechanisms for the reported association. Alone, a more liberal transfusion policy may be an insufficient intervention to target both anaemia and frailty. A complex intervention combining transfusion with more intensive rehabilitation may warrant further study. The dependency graph presented here provides a framework for further discussion of prognostic factors and proposed mechanisms underlying their reported association with functional outcome after hip fracture surgery. In this review, the graph was constructed explicitly on existing literature. Therefore, the absence of nodes, or arrows between nodes, could reflect the absence of knowledge rather than the absence of dependency [65, 66]. For example, some may argue frailty is an underrepresented mechanism for the association between several factors and functional outcome. Indeed, frail adults are more likely to present as older, with cognitive impairment, incontinence, comorbidities and poor prefracture function compared to their nonfrail counterparts [67]. Further, there was no reference to access and delivery of rehabilitation, or participation in rehabilitation, as potential mediators for the association between factors and functional outcome. This is despite evidence for an association between depression and cognitive impairment with rehabilitation participation [68]. In fact, only 16 of the 25 factors identified included any proposed mechanism underlying the studied association. We suggest this synthesis of factors on their underlying mechanisms is an important step towards transparency about underlying assumptions in prognostic analyses. Limitations The studies included in this review focused on prognostic factors of functional outcome on discharge after hip fracture surgery. Yet, focusing solely on functional outcome overlooks other forces influencing when and if a positive functional outcome occurs. Indeed, a positive functional outcome by discharge also depends on the death rate as patients may only recover if they remain alive [69]. Further, functional outcome on discharge also depends on the length of hospital stay, which varied across studies (range 1–55 days). Poor functional outcomes could reflect a higher discharge rate rather than a true difference in functional outcomes after hip fracture surgery [69]. We assigned a level of evidence to only three prognostic factors due to the high risk of bias seen across studies. It was not possible to complete a meta-analysis due to variation in eligibility criteria, prognostic factor measurement and outcome measurement. Several studies from the same patient cohort reported a positive association between prognostic factors and functional outcomes. This may suggest publication bias [25]. To reduce this potential bias we sought to include unpublished and incomplete studies. However, we identified no grey literature or incomplete studies. Additional studies may be indexed in databases not included in our search strategy. We included search terms for function, mobility and balance. We did not include search terms for surrogate measures of functional recovery, e.g., discharge destination. Additional prognostic factors may be identified by inclusion of these surrogate measures. Finally, we limited length of follow up to discharge from hospital to reduce the likelihood of unobserved factors confounding or interacting with functional outcomes after discharge from hospital. Patients continue to recover function for the first 6 months postoperatively [70, 71]. Therefore, additional prognostic factors for longer-term functional outcomes may not have been captured by this review. We followed the recommendation from Hayden et al. for quality appraisal [24]. This resulted in assigning an overall level of evidence to just three factors. A more recent study by Hayden et al. recommends assigning overall low risk of bias if the ‘most important (determined as a priori)’ of the six bias domains are rated as having low risk [23]. This would have enabled us to assign a level of evidence to additional factors. However, ranking bias domains by importance may lead to reviewer bias. More recently, overall risk was assigned based on a count of low, moderate and high risk within a study [24]. This may result in a study being judged as low overall risk of bias even if two domains are high bias. Future research should identify the optimal approach for assigning overall risk of bias in prognostic systematic reviews. Conclusion We assigned two factors a weak evidence level—anaemia on admission and cognition. We assigned Parkinson’s disease an inconclusive evidence level. Future research may target these patients by intervening directly on the prognostic factor, or the proposed modifiable underlying mechanism. We identified an additional 22 prognostic factors of functional outcomes after hip fracture surgery. However, we could not assign an evidence level to any other factors due to the high bias identified during quality assessment. Further research is required to generate high-quality prognostic studies of additional factors of functional outcomes after hip fracture surgery and their underlying mechanisms. Key points Hip fracture leads to functional impairment, institutionalisation and death. Variation in outcomes of rehabilitation may result in part from differences between patients who undergo hip fracture surgery. The strongest prognostic factors for functional outcomes were cognitive impairment and anaemia. Potential to target these patients for intervention of intensive rehabilitation or more liberal transfusion strategy. Need for high-quality prognostic studies of additional factors of functional outcome after hip fracture surgery. Supplementary Data Supplementary data mentioned in the text are available to subscribers in Age and Ageing online. Conflict of interest None. Funding None. PROSPERO Registration Number CRD42017069148. 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Nurs Health Sci 2010 ; 12 : 336 – 44 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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Age and AgeingOxford University Press

Published: Apr 12, 2018

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